20 jobs found

Company the company, a global investment bank and securities firm, has served companies and their investors for over 60 years. Headquartered in New York City, with offices in more than 25 cities around the world, the company provides clients with capital markets and financial advisory services, institutional brokerage, securities research and asset management. The firm is a leading provider of trade execution in equity, high yield, convertible and international securities for institutional investors and high net worth individuals. Role Overview the company is seeking a highly experienced Senior Full Stack / Native Cloud Engineer at Vice President level to join our London Technology team. This is a strategic, hands on engineering leadership role focused on designing and delivering scalable, cloud native, event driven platforms that enable data driven and intelligent solutions across the company' client facing business units. The role will form part of the Madison CRM & Analytics programme and will require a strong combination of deep technical expertise, end to end delivery ownership, and engineering leadership. The successful candidate will work closely with business stakeholders, product managers, and globally distributed technology teams to build resilient, high performance platforms and user facing solutions that support critical front office workflows. This role is well suited to an engineer who is comfortable operating across the full technology stack, from backend services and distributed data architecture through to responsive user interfaces, production support, and engineering best practice. Key Responsibilities Lead the design, development, and delivery of backend services and platform components using Java 8+ / Spring Boot and Python / FastAPI. Build, enhance, and operate event driven, real time data pipelines using Kafka and related streaming technologies. Provide deep technical expertise in distributed systems, data architecture, and scalable platform design. Design, implement, and maintain Java based APIs and microservices, including REST, OpenAPI, GraphQL, and gRPC services. Work with modern data technologies including PostgreSQL, MongoDB, and Amazon Redshift. Deliver reliable, performant, and responsive user interfaces aligned to UX designs, using Angular or React. Own solutions end to end, from technical design and architecture through to production deployment, monitoring, support, and continuous improvement. Champion engineering best practices across code quality, testing, CI/CD, observability, maintainability, and operational resilience. Mentor and guide junior and mid level engineers, setting high technical standards through code reviews, design reviews, and hands on technical leadership. Independently identify, analyse, scope, and propose solutions to complex technical challenges with minimal direction. Partner closely with business stakeholders, product managers, and cross functional technology teams to translate requirements into robust technical solutions. Optimise systems for performance, scalability, resiliency, reliability, and low latency operation. Participate actively in Agile ceremonies, contributing to sprint planning, estimation, execution, retrospectives, and continuous delivery improvements. Collaborate with globally distributed engineering teams to ensure consistency of architecture, delivery standards, and platform evolution. Support production systems, ensuring timely issue resolution, effective root cause analysis, and ongoing service improvement. Required Skills and Experience Strong professional experience in full stack software engineering, ideally within financial services, capital markets, or another complex enterprise technology environment. Advanced backend engineering experience with Java 8+, Spring Boot, and microservices based architectures. Strong Python development experience, preferably with FastAPI or similar modern API frameworks. Proven experience designing and building cloud native, distributed, scalable, and resilient systems. Hands on experience with Kafka or similar event streaming technologies. Strong understanding of API design and service integration patterns, including REST, OpenAPI, GraphQL, and gRPC. Practical experience with relational and NoSQL data platforms, including PostgreSQL, MongoDB, and Redshift. Frontend development experience using Angular or React, with a focus on reliable, maintainable, and responsive UI delivery. Strong understanding of software engineering best practices, including automated testing, clean code, code reviews, CI/CD, observability, and secure development practices. Experience deploying and operating production grade systems in cloud or hybrid cloud environments. Demonstrated ability to lead technical delivery, mentor engineers, and influence architecture decisions. Strong analytical and problem solving skills, with the ability to operate independently in a complex delivery environment. Excellent communication skills, with the ability to engage effectively with technical teams, business stakeholders, and product partners. Preferred Skills Experience working on CRM, client intelligence, sales enablement, or front office data platforms. Experience in investment banking, equities, fixed income, wealth management, or broader financial services technology. Familiarity with AWS or other public cloud platforms. Experience with containerisation and orchestration technologies such as Docker and Kubernetes. Knowledge of observability tooling, monitoring frameworks, distributed tracing, and production support best practices. Experience working in globally distributed Agile engineering teams. Understanding of data governance, data lineage, entitlements, and regulatory considerations in financial services environments. Candidate Profile The ideal candidate will be a hands on engineering leader who combines strong technical depth with pragmatic delivery judgement. They will be comfortable moving between architecture, coding, code reviews, stakeholder engagement, and production support. They should demonstrate ownership, intellectual curiosity, strong communication skills, and a commitment to delivering high quality technology solutions in a fast paced environment. They will be expected to set technical direction, raise engineering standards, and help build scalable platforms that support the company' client facing businesses.

Teamwork makes the stream work. Roku is changing how the world watches TV Roku is the TV streaming platform in the U.S., Canada, and Mexico, and we've set our sights on powering every television in the world. Roku pioneered streaming to the TV. Our mission is to be the TV streaming platform that connects the entire TV ecosystem. We connect consumers to the content they love, enable content publishers to build and monetize large audiences, and provide advertisers unique capabilities to engage consumers. From your first day at Roku, you'll make a valuable - and valued - contribution. We're a fast-growing public company where no one is a bystander. We offer you the opportunity to delight millions of TV streamers around the world while gaining meaningful experience across a variety of disciplines. What does the team work on? Roku's Developer Platform team builds tools and embedded capabilities that help channel partners develop, tune, and debug high-quality apps. The team works across web applications, APIs, and platform services to improve the end-to-end developer experience and support partner success at scale. What is the role? Roku is looking for a Senior Full Stack Engineer to join the Developer Platform team and build AI-enabled web applications and services that improve app development and management workflows. This role will design and deliver full stack solutions that support external partners and internal stakeholders across the Roku ecosystem. You will contribute across frontend and backend systems, with a strong focus on reliability, scalability, and usability. You will build and evolve APIs and microservices, and help integrate modern AI capabilities into production experiences where they add clear user value. The role requires strong technical judgment, cross-functional collaboration, and the ability to move from concept through delivery in a fast-paced environment. You will join a high-performing team with a strong delivery culture and a commitment to building practical, high-impact developer tools. How will I use AI at Roku? At Roku, we don't just use AI, we work with it. AI agents and smart tools help power drafts, analysis, and repetitive workflows, while our people bring direction, judgment, and accountability. We're looking for curious, adaptable builders who can show how they've used AI or automation to move faster, raise the bar, and scale their impact. We value your AI skills if you have built fluency across the agentic engineering toolchain - coding harnesses like Claude Code or Cursor, MCP servers, custom skills, or agent frameworks - and can describe projects where you shipped real work with these tools. You know how to drive an agent, verify its output, and ramp on an unfamiliar codebase with an agent helping you. What are the responsibilities of the role? Design and build full stack web applications using React and Node.js Integrate AI capabilities including LLM-driven experiences where appropriate Develop APIs and microservices that connect tools, data, and platform workflows Deploy, scale, and monitor services in cloud environments using Kubernetes Build robust, highly available backend and frontend systems for developer-facing use cases Collaborate with cross-functional teams to define and deliver partner and internal tooling Troubleshoot production issues and improve performance and reliability Participate in code reviews and contribute to engineering best practices What experience would help someone be successful in this role at Roku? Proven full stack engineering experience with production web applications Strong skills in TypeScript, JavaScript, React, and Node.js Experience with backend development in Python or Go and frameworks such as FastAPI Familiarity with PostgreSQL, Redis, and REST API design and integration Experience with test-driven development and CI/CD workflows Experience integrating AI technologies such as OpenAI, LangChain, or RAG pipelines Understanding of authentication and authorization approaches including OpenID and SAML Experience deploying cloud-native services on AWS with containerized infrastructure and Kubernetes Experience with message queuing systems such as RabbitMQ or Apache Kafka Demonstrated AI/agentic-tooling fluency per the section above Bachelor's or Master's degree in Computer Science, Electronics, Communications, or a related field What's Roku's approach to hybrid working? Roku fosters an inclusive and collaborative environment where teams generally work in the office Monday through Thursday. Fridays are generally flexible for remote work, except for employees whose specific roles or assigned office location require five days' a week attendance. What are some of the benefits? Roku is committed to offering a diverse range of benefits as part of our compensation package to support our employees and their families. Our comprehensive benefits include global access to mental health and financial wellness support and resources. Local benefits include statutory and voluntary benefits which may include healthcare (medical, dental, and vision), life, accident, disability, commuter, and retirement options (401(k)/pension). Employees are supported in taking time off, in accordance with local leave policies and other personal needs to support their evolving work and life needs. It's important to note that not every benefit is available in all locations or for every role. For details specific to your location, please consult with your recruiter. Accommodations Roku welcomes applicants of all backgrounds and provides reasonable accommodations and adjustments in accordance with applicable law. If you require reasonable accommodation at any point in the hiring process, please direct your inquiries to . What should I know about Roku's culture? Roku is a great place for people who want to work in a fast-paced environment where everyone is focused on the company's success rather than their own. We try to surround ourselves with people who are great at their jobs, who are easy to work with, and who keep their egos in check. We appreciate a sense of humor. We believe a fewer number of very talented folks can do more for less cost than a larger number of less talented teams. We're independent thinkers with big ideas who act boldly, move fast and accomplish extraordinary things through collaboration and trust. In short, at Roku you'll be part of a company that's changing how the world watches TV. We have a unique culture that we are proud of. We think of ourselves primarily as problem-solvers, which itself is a two-part idea. We come up with the solution, but the solution isn't real until it is built and delivered to the customer. That penchant for action gives us a pragmatic approach to innovation, one that has served us well since 2002. To learn more about Roku, our global footprint, and how we've grown, visit By providing your information, you acknowledge that you want Roku to contact you about job roles, that you have read Roku's Applicant Privacy Notice, and understand that Roku will use your information as described in that notice. If you do not wish to receive any communications from Roku regarding this role or similar roles in the future, you may unsubscribe at any time by emailing .

About Us At Plentific, we're redefining property management in real time. Our mission, is to lead real estate through the transformative journey into "The World of Now," enabling us to empower property professionals through our innovative, cloud based platform. We harness cutting edge technology and data driven insights to streamline operations for landlords, letting agents, and property managers-enabling them to optimize maintenance, manage repairs, and make informed decisions instantly. Our platform is designed to create seamless, real time workflows that transform traditional property management into a dynamic, digital experience. Backed by a world class group of investors-including Noa, Highland Europe, Brookfields, Mubadala, RXR Digital Ventures, and Target Global-Plentific is at the forefront of the proptech revolution. Headquartered in London with a global outlook, we're continually expanding our reach and impact. We're looking for forward thinking, passionate professionals who are ready to contribute to our mission and drive industry innovation. If you're excited about making an immediate impact and shaping the future of property management, explore career opportunities with us at Plentific. The Role We're looking for a Software Architect to join our engineering team and play a pivotal role in shaping the technical direction of our platform. This is not just a hands on engineering role, it's a leadership position where you'll be expected to bridge the gap between product vision and technical execution. You'll work closely with Product Managers to translate business requirements into robust technical strategies, produce detailed technical analyses, and guide a team of engineers toward successful, on time delivery. At the same time, you'll remain deeply hands on, contributing directly to our codebase and setting the bar for engineering excellence across the team. Our engineering team sits at the centre of everything we do at Plentific and is constantly tackling challenging problems, such as online payments, quoting, invoicing, booking, search and scoring algorithms, ETL, data pipelines, in app messaging, real time notifications, and fraud prevention. Our backend engineers mostly work with Python and Django on a service oriented architecture deployed at scale on Kubernetes. The rest of the tech stack includes Django REST Framework, FastAPI, PostgreSQL, AWS, React.js, Docker, Redis, Celery, Pandas, NumPy, Git, Jenkins, and Elasticsearch. We put significant emphasis on design patterns, code readability, automated testing, maintainability, and extensibility. As Software Architect, you'll be the standard bearer for these values. At Plentific AI is at the core of how we build and deliver software. We expect our Software Architect to be fluent in AI assisted development practices, leveraging AI tools across the entire engineering lifecycle: from spec driven development and architectural design, to coding, code review, and delivery. Responsibilities Technical Leadership & Strategy Collaborate closely with Product Managers to translate product requirements into comprehensive technical analyses, breaking down complexity into clear, actionable engineering plans with the help of AI spec driven development tools Define and own the technical roadmap for your team, ensuring architectural decisions align with business goals and long term platform scalability Guide and mentor engineers throughout the delivery lifecycle, from design through to deployment, ensuring the team stays on track and produces high quality output Act as the primary technical point of contact for your squad, facilitating alignment between engineering, product, and stakeholders Architecture & Design Design and evolve scalable, resilient microservices architectures using Django and Python, deployed on Kubernetes at scale Lead the design of APIs, data pipelines, and distributed systems with a strong focus on performance, reliability, and maintainability Define and enforce best practices around database design, query optimisation, and data modelling across relational databases (PostgreSQL) Evaluate emerging technologies and architectural patterns, making evidence based recommendations to the broader engineering organisation Hands On Engineering Write well formulated, testable, and readable code using appropriate software design patterns Build and maintain APIs, microservices, and data pipelines Write complex SQL queries and optimise database performance Debug and resolve issues across our applications, including production incidents Review, maintain, and refactor existing code to support improved or new features AI Driven Development Champion and embed AI assisted practices across the full development lifecycle, including spec generation, architectural design, coding, and delivery, ensuring the team operates at the frontier of modern, AI augmented engineering Delivery & Collaboration Lead code reviews, setting a high bar for quality and consistency across the team Work with product owners, engineering managers, UI designers, and engineers to produce technical specifications and project documentation Remove technical blockers and proactively surface risks to delivery, proposing pragmatic solutions Write clear technical documentation for code, algorithms, APIs, and system architecture Experience and Qualifications 8+ years of software engineering experience, with a strong focus on Python and Django. Proven, hands on experience building and operating Django based microservices at scale, running in production on Kubernetes. Demonstrable experience with AI tools to assist Software Development and Architectural document writing (e.g. Claude Code, Cursor). Demonstrable experience in a Tech Lead or Software Architect capacity, owning technical direction and guiding teams toward delivery. Strong track record of producing technical analyses: working alongside Product Managers to assess requirements, define solutions, estimate complexity, and produce clear, actionable engineering plans. Deep knowledge of distributed systems design, including event driven architectures, asynchronous processing (e.g. Celery, Redis), and inter service communication patterns. Expert level understanding of relational database management (PostgreSQL preferred), including schema design, normalisation, and query optimisation. Solid grasp of computer science fundamentals: data structures, algorithms, and software design patterns. Experience with AWS and cloud native infrastructure; familiarity with CI/CD pipelines (e.g. Jenkins). Ability to work UK working hours (+/- 3 hours). Excellent communication skills, with the ability to articulate complex technical concepts clearly to both technical and non technical audiences. A collaborative, can do mindset with strong ownership and accountability. Benefits A competitive compensation package 25 days annual holiday + 1 additional day for every year served up to 5 years. Flexible working environment including the option to work abroad Private health care for you and immediate family members with discounted gym membership, optical, dental and private GP Enhanced parental leave Life insurance (4x salary) Employee assistance program Company volunteering day and charity salary sacrifice scheme Learning management system powered by Udemy Referral bonus and charity donation if someone you introduce joins the company Season ticket loan, Cycle to work, Electric vehicle and Techscheme programs Pension scheme Work abroad scheme Company sponsored lunches, dinners and social gatherings Fully stocked kitchen with drinks, snacks, fruit, breakfast cereal etc.

United States Digital Space LLC in London seeks a senior Python backend developer to design and build scalable microservices. You will work on an application for a major trader, contributing to architecture, integration, and deployment strategies. The role requires deep Python expertise (FastAPI, SQLAlchemy) and experience with microservices, data handling, and code quality. This on-site position offers growth in a dynamic commodities environment.

Project description An excellent opportunity for personal development in a dynamic environment. You will join a highly skilled and dynamic team, developing an application for one of the largest traders in the world. There are good opportunities to develop in different areas. The team is highly skilled and will provide a great opportunity to expand your knowledge in the commodities space. We require talented and enthusiastic fast learners to join us and learn with the team. The project is a long-term one and developing and expanding fast. It will support significant development and change in the future, expecting to expand the existing application by 3-4 times. You will be working in one of the most influential trading houses in the world. Do you have what it takes? Then get in touch. Responsibilities Application Design and Integration: Design application components to meet business requirements and document the design. Define the integration strategy, including rationale and environment requirements, and establish the sequence for product-component integration. Assess risks related to design, integration, and data quality, and identify mitigation strategies. Participate in design reviews and ensure adherence to development standards reflecting the bank's guidelines (e.g., naming conventions, encryption, security). Implement architectural changes as defined by architects. Contribute to root cause analysis and problem solving. Python Development: Develop source code for software components based on detailed specifications and design documents. Participate in code reviews to resolve findings collaboratively. Integrate software components according to the group's strategy and verify them through unit and integration testing for python. Track and record all code changes through the change management process, ensuring development is scheduled and approved. Develop methods for deploying change items and managing release deployments in non production environments. Create and maintain deployment notes, user guides, and training materials for software products. Ensure document consistency with software product releases. Fix software defects and analyze code quality. Collaborate with functional analysts and technical specialists as needed. Develop Python microservices. Experience with SQL database and caching technologies. Required Skills Python (libraries: FastAPI, pandas, SQLAlchemy) Micro service architecture Nice to have Angular with TypeScript Languages English: C1 Advanced Seniority: Senior Location: London, United Kingdom of Great Britain and Northern Ireland

Senior Software Engineer - Pricing AI (Manchester) The Role We are seeking a talented Senior Developer with a strong focus on Python-based AI/ML development, automation, and general software engineering. The successful candidate will play a key role in building and deploying machine learning features and data-driven applications. You will work on end-to-end solutions - from writing robust code and unit tests to developing APIs and integrating machine learning models into our product ecosystem. This role requires a mix of software engineering excellence, an eye for automation, and hands on experience with AI/ML frameworks. If you are passionate about leveraging Python to solve complex problems and deliver scalable AI solutions, we want to hear from you. Experience in the travel or retail industry would be an advantage. Responsibilities Design, implement, and maintain software components that incorporate machine learning algorithms and data processing, and develop clean, efficient Python code for both backend logic and integration of ML models. Understand the business drivers behind each feature. Create and optimise data pipelines to collect, preprocess, and transform data for machine learning and analytics; work with large datasets, ensuring data quality and availability for training and prediction tasks. Develop robust RESTful APIs and microservices (using frameworks like FastAPI or Flask) to expose machine learning functionalities and data services; ensure APIs are secure, well documented, and perform at scale. Write and maintain comprehensive tests for your code; use PyTest for unit testing and Selenium (where appropriate) for end to end or UI testing to automate quality assurance; ensure that new features have proper test coverage and meet quality standards before deployment. Collaborate with DevOps engineers to set up and maintain CI/CD pipelines for building, testing, and deploying applications and ML models; containerise applications (Docker) and assist in orchestration (Kubernetes or cloud services) to ensure smooth deployment of scalable solutions. Work closely with data scientists to deploy machine learning models into production environments; optimise model inference performance (leveraging frameworks like TensorFlow or PyTorch for model serving) and implement monitoring to track model performance, accuracy, and reliability post deployment. Keep up to date with the latest developments in Python, AI/ML technologies, and software engineering best practices; proactively suggest improvements to systems and processes, and contribute to architectural decisions that enhance the capabilities or performance of our AI solutions. Provide technical guidance and mentorship to Junior Engineers. Qualifications Bachelor's degree in Computer Science, Engineering, or related field (or equivalent work experience); a Master's degree or specialization in Artificial Intelligence/Machine Learning is a plus. Must have 8 years' experience working as a Software Engineer on large software applications. Proficient in technologies including Python, REST, PyTorch, TensorFlow, Docker, FastAPI, Selenium, React, TypeScript, Redux, GraphQL, Kafka, and Apache Spark. Experience working with one or more of the following database systems: DynamoDB, DocumentDB, MongoDB. Demonstrated expertise in unit testing and tools such as JUnit, Mockito, PyTest, and Selenium. Strong working knowledge of the PyData stack-pandas, NumPy for data manipulation; Jupyter Notebooks for experimentation; matplotlib/Seaborn for basic visualisation, and experience with data analysis and troubleshooting data related issues. Knowledge of design patterns and software architectures. Familiarity with CI/CD and automation tools; experience using Git for version control and platforms like Bitbucket for code collaboration; knowledge of build tools and pipeline configuration (Jenkins) to automate testing and deployment. Strong problem solving and analytical skills. Presentation and teamwork skills. Understanding of both Waterfall and Agile methodologies.

BXTI - Liquid Credit, Full Stack Software Engineer, AssociateApplylocations: Londontime type: Full timeposted on: Posted 5 Days Agojob requisition id: 43115Blackstone is the world's largest alternative asset manager. We seek to create positive economic impact and long-term value for our investors, the companies we invest in, and the communities in which we work. We do this by using extraordinary people and flexible capital to help companies solve problems. Our $1.1 trillion in assets under management include investment vehicles focused on private equity, real estate, public debt and equity, infrastructure, life sciences, growth equity, opportunistic, non-investment grade credit, real assets and secondary funds, all on a global basis. Further information is available at . on LinkedIn, X, and Instagram. Business Unit: Blackstone Technology & Innovations (BXTI) is the technology team at the core of each of Blackstone's businesses and new growth initiatives. Serving both internal and external clients, we work to build the next generation of systems that manage risk, create efficiency and improve transparency within the firm and across our broad community of investors and portfolio companies.BXTI is nimble and entrepreneurial - our open, iterative design processes and rapid pace of development mean that everyone on the team has the opportunity to make an impact from day one. We are problem solvers who can take projects from idea to implementation. We believe in active mentoring and developing excellence. We collaborate to find the best answers for our customers and for Blackstone. We are critical to the firm maintaining its competitive edge. Job Title: Associate Job Description: The Liquid Credit Technology team develops modern fixed-income asset management systems including portfolio management system, order management system, execution management system, and trade processing to support Liquid Credit Strategies ("LCS") business. LCS manages $114B in AUM across diversified portfolios of fixed income investments, such as bank loans, high yield bonds, CDS/CDX, Future, Repo, CMBS/RMBS, CLO debt and equity tranches. The new hire will be a key member of the team developing software solutions for the portfolio managers and traders.Our existing applications are built on a highly scalable microservices architecture deployed on a cloud-hosted containerized environment. Key technologies in our stack include C#, React/Angular, Typescript, FastAPI, Python, Terraform, SQL, AWS ECS, AWS Lambda, AWS DynamoDB , AWS SNS/SQS, CI/CD tooling (e.g., Gitlab Runners), and data warehouse solutions like Snowflake. Qualifications: We seek to hire individuals who are highly motivated, intelligent, and have demonstrated excellence in prior endeavors. In addition, the successful candidate should have: 3+ years of proven software development experience in relevant industry, with proficiency in C#, JavaScript (React and/or Angular), Typescript, databases (relational and/or NoSQL), and cloud technologies, preferably AWS. Experience with RESTful API design, development, and scalable microservice architectures Ability to develop scalable, secure, and maintainable code, with a strong background in object-oriented programming Excellent problem-solving skills and strong communication skills Self-starter with an entrepreneurial attitude, willing to teach and mentor others, and desire to work in a fast-paced team environment Experience with automation testing approaches and performance testing Experience with fixed-income front-office trading systems Bachelor's degree (BSc/BA) or above in Computer Science, Engineering, or a related field. Responsibilities: Use cloud native technologies and services to build scalable, reliable, and secure applications Build, support, and integrate web applications, microservices, and data pipelines on a variety of platforms with high code quality. Write automated unit, integration, and deployment tests. Utilize standard CI/CD tooling (i.e. GitLab Runners) to build and deploy application code in various environments. Use modern software development methodologies and tools like JIRA to manage and deliver projects Participate in technical design, code reviews, and agile ceremonies, and troubleshoot software defects. Provide technical support, automate repetitive tasks, and stay updated with industry trends and emerging technologies. Mentor and train junior developers, contribute to the collaborative team culture, and demonstrate a willingness to learn from others.The duties and responsibilities described here are not exhaustive and additional assignments, duties, or responsibilities may be required of this position. Assignments, duties, and responsibilities may be changed at any time, with or without notice, by Blackstone in its sole discretion.Blackstone is committed to providing equal employment opportunities to all employees and applicants for employment without regard to race, color, creed, religion, sex, pregnancy, national origin, ancestry, citizenship status, age, marital or partnership status, sexual orientation, gender identity or expression, disability, genetic predisposition, veteran or military status, status as a victim of domestic violence, a sex offense or stalking, or any other class or status in accordance with applicable federal, state and local laws. This policy applies to all terms and conditions of employment, including but not limited to hiring, placement, promotion, termination, transfer, leave of absence, compensation, and training. All Blackstone employees, including but not limited to recruiting personnel and hiring managers, are required to abide by this policy.If you need a reasonable accommodation to complete your application, please contact Human Resources at (US), (0) (EMEA) or (APAC).Depending on the position, you may be required to obtain certain securities licenses if you are in a client facing role and/or if you are engaged in the following: Attending client meetings where you are discussing Blackstone products and/or and client questions; Marketing Blackstone funds to new or existing clients; Supervising or training securities licensed employees; Structuring or creating Blackstone funds/products; and Advising on marketing plans prepared by a sales team or developing and/or contributing information for marketing materials. Note: The above list is not the exhaustive list of activities requiring securities licenses and there may be roles that require review on a case-by-case basis. Please speak with your Blackstone Recruiting contact with any questions. To submit your application please complete the form below. Fields marked with a red asterisk must be completed to be considered for employment (although some can be answered "prefer not to say"). Failure to provide this information may compromise the follow-up of your application. When you have finished click Submit at the bottom of this form.

Overview Architect and lead the implementation of multi-agent systems using Google AI SDKs (Vertex AI Agent Builder), LangGraph, CrewAI, and other emerging orchestration frameworks. Design and build stateful, tool-augmented agents capable of advanced reasoning, long-term planning, and autonomous execution. Develop and document agent orchestration patterns including planner-executor, supervisor-worker, and hierarchical agent structures. Implement sophisticated memory systems (short-term, long-term, and cross-session contextual memory). Enable seamless cross-agent communication and multi-modal coordination. Lead the delivery of production-grade LLM applications: RAG pipelines, specialised agents, and developer copilots. Integrate diverse tools, enterprise APIs, and legacy systems into agentic workflows. Design robust system prompts, dynamic routing logic, and AI guardrails using Vertex AI Model Garden or Azure AI Studio. Drive optimisation of AI workflows for latency, token cost, and output quality. Develop and own reusable AI microservices, agent frameworks, and standardised APIs. Contribute to core AI platform capabilities including model routing, centralised observability, and safety filters. Define and enforce engineering standards and best practices for AI development across the team. Deploy and manage agent-based systems on GCP, Azure, and/or AWS using Docker, Kubernetes (GKE/AKS/EKS), and Cloud Run. Implement comprehensive monitoring and observability using Vertex AI Inspector, LangSmith, or Azure Monitor. Drive incident response and post-mortems for production AI system failures. Act as a technical lead on key AI engineering workstreams, shaping architecture and approach. Mentor and support more junior AI engineers through code review, design discussions, and pair programming. Collaborate with Principal AI Engineer and cross-functional teams (data, product, delivery) to align AI engineering with business outcomes. Stay at the forefront of the rapidly evolving agentic AI landscape and bring new approaches into the team. Requirements 5-8 years of software engineering experience with at least 3 years focused on LLM-based or AI systems in production. Proven track record building and shipping RAG pipelines, autonomous agents, and multi-step reasoning chains. Strong hands-on experience with Google AI SDKs, Vertex AI, and/or Azure AI services. Deep proficiency in orchestration stacks: LangGraph, CrewAI, LlamaIndex, Haystack, or comparable frameworks. Expert-level Python; strong backend development skills (FastAPI, Go, or Node.js). Deep understanding of agent design patterns: planning, reflection, memory, and tool-use. Experience integrating complex enterprise APIs and event-driven systems into agentic workflows. Proven ability to trace, debug, and improve non-deterministic, multi-step AI reasoning pipelines. Strong instinct for building resilient, observable, and production-ready AI systems. Strong familiarity with GCP and/or Azure core services: GKE, Cloud Run, Azure AI services. Infrastructure as Code: Terraform or Pulumi. CI/CD: experience building automated evaluation and deployment pipelines for AI models. ATS Optimization Keywords Hard Skills Python FastAPI Go Node.js Google AI SDKs Vertex AI Azure AI services LangGraph CrewAI RAG pipelines Soft Skills leadership mentoring collaboration problem-solving communication design discussions code review incident response optimisation best practices

• Architect and lead the implementation of multi-agent systems using Google AI SDKs (Vertex AI Agent Builder), LangGraph, CrewAI, and other emerging orchestration frameworks. • Design and build stateful, tool-augmented agents capable of advanced reasoning, long-term planning, and autonomous execution. • Develop and document agent orchestration patterns including planner-executor, supervisor-worker, and hierarchical agent structures. • Implement sophisticated memory systems (short-term, long-term, and cross-session contextual memory). • Enable seamless cross-agent communication and multi-modal coordination. • Lead the delivery of production-grade LLM applications: RAG pipelines, specialised agents, and developer copilots. • Integrate diverse tools, enterprise APIs, and legacy systems into agentic workflows. • Design robust system prompts, dynamic routing logic, and AI guardrails using Vertex AI Model Garden or Azure AI Studio. • Drive optimisation of AI workflows for latency, token cost, and output quality. • Develop and own reusable AI microservices, agent frameworks, and standardised APIs. • Contribute to core AI platform capabilities including model routing, centralised observability, and safety filters. • Define and enforce engineering standards and best practices for AI development across the team. • Deploy and manage agent-based systems on GCP, Azure, and/or AWS using Docker, Kubernetes (GKE/AKS/EKS), and Cloud Run. • Implement comprehensive monitoring and observability using Vertex AI Inspector, LangSmith, or Azure Monitor. • Drive incident response and post-mortems for production AI system failures. • Act as a technical lead on key AI engineering workstreams, shaping architecture and approach. • Mentor and support more junior AI engineers through code review, design discussions, and pair programming. • Collaborate with Principal AI Engineer and cross-functional teams (data, product, delivery) to align AI engineering with business outcomes. • Stay at the forefront of the rapidly evolving agentic AI landscape and bring new approaches into the team. Requirements 5-8 years of software engineering experience with at least 3 years focused on LLM-based or AI systems in production. Proven track record building and shipping RAG pipelines, autonomous agents, and multi-step reasoning chains. Strong hands-on experience with Google AI SDKs, Vertex AI, and/or Azure AI services. Deep proficiency in orchestration stacks: LangGraph, CrewAI, LlamaIndex, Haystack, or comparable frameworks. Expert-level Python; strong backend development skills (FastAPI, Go, or Node.js). Deep understanding of agent design patterns: planning, reflection, memory, and tool-use. Experience integrating complex enterprise APIs and event-driven systems into agentic workflows. Proven ability to trace, debug, and improve non-deterministic, multi-step AI reasoning pipelines. Strong instinct for building resilient, observable, and production-ready AI systems. Strong familiarity with GCP and/or Azure core services: GKE, Cloud Run, Azure AI services. Infrastructure as Code: Terraform or Pulumi. CI/CD: experience building automated evaluation and deployment pipelines for AI models. ATS Optimization Keywords Below are skills and terms extracted directly from this job posting to improve Applicant Tracking System (ATS) visibility. This unique feature helps candidates tailor their applications more effectively - a feature exclusive to JobTailor job listings. Hard Skills Python FastAPI Go Node.js Google AI SDKs Vertex AI Azure AI services LangGraph CrewAI RAG pipelines Soft Skills leadership mentoring collaboration problem-solving communication design discussions code review incident response optimisation best practices

About Charlotte Tilbury Beauty Founded by British makeup artist and beauty entrepreneur Charlotte Tilbury MBE in 2013, Charlotte Tilbury Beauty has revolutionised the face of the global beauty industry by de-coding makeup applications for everyone, everywhere, with an easy-to-use, easy-to-choose, easy-to-gift range. Today, Charlotte Tilbury Beauty continues to break records across countries, channels, and categories and to scale at pace. Over the last 10 years, Charlotte Tilbury Beauty has experienced exceptional growth and is one of the most talked about brands in the beauty industry and beyond. It has become a global sensation across 50 markets (and growing), with over 2,300 employees globally who are part of the Dream Team making the magic happen. Today, Charlotte Tilbury Beauty is a truly global business, delivering market-leading growth, innovative retail and product launches fuelled by industry-leading tech - all with an internal culture of embracing challenges, disruptive thinking, winning together, and sharing the magic. The energy behind the brand is infectious, and as we grow, we are always looking for extraordinary talent who want to be part of this our success and help drive our limitless ambitions. About the role The AI & ML Engineering team accelerates the adoption of AI across the business, championing innovation while ensuring our machine learning solutions are robust, scalable, and cost-efficient. We enable teams to solve problems using existing AI tools where possible and build custom solutions when needed. Our remit spans AI enablement, agentic systems development, and "conventional" ML engineering for non-GenAI applications e.g. recommender systems, forecasting models, and more. We're looking for an AI & ML Engineer who is passionate about building production-ready AI and machine learning solutions. You'll work across a variety of AI initiatives, contributing to the design, implementation and deployment of scalable AI systems. You will be expected to deliver high-quality AI/ML solutions across the full development lifecycle, from proof of concept through to production and ongoing optimisation. Working closely with other engineers and stakeholders across the business, you'll contribute to building reusable platforms, services and best practices while continuously developing your technical expertise. This role reports to the Lead AI & ML Engineer and sits within the Data function, working as part of a specialist AI engineering team. You'll contribute to a mix of dedicated AI initiatives and larger cross-functional projects alongside colleagues from Technology, Data and Product. As a AI & ML Engineer you will The role covers the full AI/ML engineering lifecycle, from discovery to deployment and monitoring. Responsibilities include Designing and implementing agentic systems using techniques spanning RAG, grounding, prompt engineering, and orchestration on a GCP-first stack. Building and maintaining production ML pipelines and services for non-GenAI use cases (e.g. recommender systems, customer segmentation models, marketing optimisation modules, leveraging supervised, unsupervised and/or econometric modelling approaches). Developing APIs and microservices for AI/ML solutions, ensuring security, scalability, and observability. Implementing CI/CD for ML services, writing infrastructure as code, and monitoring for model/data drift and performance. Establishing robust guardrails for safe AI usage, including prompt security, practical evaluation frameworks, and compliance with privacy regulations. Contributing to reusable components, documentation and engineering best practices that improve AI/ML delivery across the organisation. Collaborating with data engineers, data scientists, front & back-end engineers, product managers to deliver impactful solutions. Supporting the evaluation of new AI technologies, frameworks and tooling, contributing ideas and recommendations for continuous improvement. Who you will work with Data and AI Team About you The role requires a blend of technical depth and product sense, including Strong Python engineering skills (FastAPI, testing, typing) and experience with cloud-native development (GCP preferred). Hands-on experience with GCP Vertex AI (model endpoints, pipelines, embeddings, vector search) or equivalent cloud-native AI/ML platforms (e.g. AWS SageMaker, AzureML) and agent orchestration frameworks (e.g. LangChain, LangGraph, ADK). Solid understanding of MLOps - CI/CD, IaC (Terraform), experiment tracking, model registry, and monitoring. Proven experience deploying and operating ML systems in production (batch and real-time). Familiarity with RAG architectures, prompt engineering, guardrails and evaluation techniques. Previous experience developing agentive capabilities, such as agent skills, MCP servers, tool usage. Strong grasp of security, privacy, and governance principles (IAM, secrets, PII handling). Effective communication skills and ability to work with both technical and non-technical stakeholders. An interest in evaluating new AI technologies and contributing to technical discussions around build, buy or configure decisions. Bachelor's or Master's degree in Computer Science/Engineering/related field, or demonstrable relevant experience. In addition to the above, we would LOVE if you have Knowledge of vector databases and retrieval strategies. Experience with recommender systems and ranking models. Familiarity with LLM evaluation tools (e.g., RAGAS, TruLens, LangSmith, Arize). A working understanding of cloud networking and platform infrastructure. Experience in e-commerce or retail environments. Why join us? Be a part of this values driven, high growth, magical journey with an ultimate vision to empower everyone, everywhere to be the best version of themselves. We're a hybrid model with flexibility, allowing you to work how best suits you. 25 days holiday (plus bank holidays) with an additional day to celebrate your birthday. Inclusive parental leave policy that supports all parents and carers throughout their parenting and caring journey. Financial security and planning with our pension and life assurance for all. Wellness and social benefits including Medicash, Employee Assist Programs and regular social connects with colleagues. Bring your fury friend to work with you on our allocated dog-friendly days and spaces and not to forget our generous product discount and gifting! At Charlotte Tilbury Beauty, our mission is to empower everybody in the world to be the most beautiful version of themselves. We celebrate and support this by encouraging and hiring people with diverse backgrounds, cultures, voices, beliefs, and perspectives into our growing global workforce. By doing so, we better serve our communities, customers, employees - and the candidates that take part in our recruitment process.

About Charlotte Tilbury Beauty Founded by British makeup artist and beauty entrepreneur Charlotte Tilbury MBE in 2013, Charlotte Tilbury Beauty has revolutionised the face of the global beauty industry by de-coding makeup applications for everyone, everywhere, with an easy-to-use, easy-to-choose, easy-to-gift range. Today, Charlotte Tilbury Beauty continues to break records across countries, channels, and categories and to scale at pace. Over the last 10 years, Charlotte Tilbury Beauty has experienced exceptional growth and is one of the most talked about brands in the beauty industry and beyond. It has become a global sensation across 50 markets (and growing), with over 2,300 employees globally who are part of the Dream Team making the magic happen. Today, Charlotte Tilbury Beauty is a truly global business, delivering market-leading growth, innovative retail and product launches fuelled by industry-leading tech - all with an internal culture of embracing challenges, disruptive thinking, winning together, and sharing the magic. The energy behind the brand is infectious, and as we grow, we are always looking for extraordinary talent who want to be part of this our success and help drive our limitless ambitions. About the role The AI & ML Engineering team accelerates the adoption of AI across the business,championing innovation while ensuring our machine learningsolutions are robust, scalable, and cost-efficient. We enable teams to solve problems using existing AI tools where possible and build custom solutionswhen needed. Our remit spans AI enablement, agentic systems development, and "conventional" ML engineering for non-GenAI applicationse.g.recommender systems, forecasting models, and more. We're looking for an AI & ML Engineer who is passionate about building production-ready AI and machine learning solutions.You'llwork across a variety of AI initiatives, contributing to the design,implementationand deployment of scalable AI systems. You will be expected to deliver high-quality AI/ML solutions across the full development lifecycle, from proof of concept through to productionand ongoing optimisation. Working closely withotherengineersand stakeholders across the business,you'llcontribute to building reusable platforms, services and best practices while continuously developing your technicalexpertise. This role reports to the Lead AI & ML Engineer andsits within the Data function, working as part of a specialist AI engineering team.You'llcontribute to a mix of dedicated AI initiatives and larger cross-functional projects alongside colleagues from Technology, Data andProduct. As a AI & ML Engineer you will The role covers the full AI/ML engineering lifecycle, from discovery to deployment and monitoring. Responsibilities include Designing and implementing agentic systems using techniques spanning RAG, grounding, prompt engineering, and orchestration on a GCP-first stack. Building andmaintainingproduction ML pipelines and services for non-GenAI use cases (e.g.recommendersystems, customer segmentation models,marketing optimisation modules,leveragingsupervised,unsupervisedand/or econometric modelling approaches). Developing APIs and microservices for AI/ML solutions, ensuring security, scalability, and observability. Implementing CI/CD for MLservices,writinginfrastructure as code, and monitoring for model/data drift and performance. Establishingrobustguardrails for safe AI usage, including prompt security,practicalevaluation frameworks, and compliance with privacy regulations. Contributing to reusable components, documentation and engineering best practices that improve AI/ML delivery across theorganisation. Collaborating with data engineers,data scientists,front & back-end engineers,productmanagersto deliver impactful solutions. Supporting the evaluation of new AI technologies, frameworks and tooling, contributing ideas and recommendations for continuous improvement. Who you will work with Data and AI Team About you The role requires a blend of technical depth and product sense, including Strong Python engineering skills (FastAPI, testing,typing) and experience with cloud-native development (GCP preferred). Hands-on experience with GCP Vertex AI(model endpoints, pipelines, embeddings, vector search)or equivalent cloud-nativeAI/ML platforms (e.g. AWS SageMaker, AzureML) andagentorchestration frameworks(e.g.LangChain,LangGraph, ADK). Solid understanding ofMLOps - CI/CD,IaC(Terraform), experiment tracking, model registry, and monitoring. Proven experience deploying and operating MLsystemsin production (batch and real-time). Familiarity with RAG architectures, prompt engineering,guardrailsand evaluation techniques. Previousexperience developing agentic capabilities,such asagentskills, MCP servers,tool usage. Strong grasp of security, privacy, and governance principles (IAM, secrets, PII handling). Effectivecommunication skills and ability to work withboth technical andnon-technicalstakeholders. An interest in evaluating new AI technologies and contributing to technical discussions around build, buy or configure decisions. Bachelor's orMaster's degree in Computer Science/Engineering/related field, or demonstrable relevant experience. In addition to the above, we would LOVE if youhave Knowledge ofvector databases and retrieval strategies. Experience withrecommender systems and ranking models. Familiarity with LLM evaluation tools (e.g., RAGAS,TruLens,LangSmith,Arize). A working understanding of cloud networking and platform infrastructure. Experience in e-commerce or retail environments. Why join us? Be a part of this values driven, high growth, magical journey with an ultimate vision to empower everyone, everywhere to be the best version of themselves. We're a hybrid model with flexibility, allowing you to work how best suits you. 25 days holiday (plus bank holidays) with an additional day to celebrate your birthday. Inclusive parental leave policy that supports all parents and carers throughout their parenting and caring journey. Financial security and planning with our pension and life assurance for all. Wellness and social benefits including Medicash, Employee Assist Programs and regular social connects with colleagues. Bring your fury friend to work with you on our allocated dog friendly days and spaces and not to forget our generous product discount and gifting! At Charlotte Tilbury Beauty, our mission is to empower everybody in the world to be the most beautiful version of themselves. We celebrate and support this by encouraging and hiring people with diverse backgrounds, cultures, voices, beliefs, and perspectives into our growing global workforce. By doing so, we better serve our communities, customers, employees - and the candidates that take part in our recruitment process.

About the role The AI & ML Engineering team accelerates the adoption of AI across the business, championing innovation while ensuring our machine learning solutions are robust, scalable, and cost-efficient. We enable teams to solve problems using existing AI tools where possible and build custom solutions when needed. Our remit spans AI enablement, agentic systems development, and "conventional" ML engineering for non-GenAI applications e.g. recommender systems, forecasting models, and more. We're looking for an AI & ML Engineer who is passionate about building production ready AI and machine learning solutions. You'll work across a variety of AI initiatives, contributing to the design, implementation and deployment of scalable AI systems. You will be expected to deliver high-quality AI/ML solutions across the full development lifecycle, from proof of concept through to production and ongoing optimisation. Working closely with other engineers and stakeholders across the business, you'll contribute to building reusable platforms, services and best practices while continuously developing your technical expertise. This role reports to the Lead AI & ML Engineer and sits within the Data function, working as part of a specialist AI engineering team. You'll contribute to a mix of dedicated AI initiatives and larger cross functional projects alongside colleagues from Technology, Data and Product. Responsibilities The role covers the full AI/ML engineering lifecycle, from discovery to deployment and monitoring. Responsibilities include Designing and implementing agentic systems using techniques spanning RAG, grounding, prompt engineering, and orchestration on a GCP first stack. Building and maintaining production ML pipelines and services for non GenAI use cases (e.g. recommender systems, customer segmentation models, marketing optimisation modules, leveraging supervised, unsupervised and/or econometric modelling approaches). Developing APIs and microservices for AI/ML solutions, ensuring security, scalability, and observability. Implementing CI/CD for ML services, writing infrastructure as code, and monitoring for model/data drift and performance. Establishing robust guardrails for safe AI usage, including prompt security, practical evaluation frameworks, and compliance with privacy regulations. Contributing to reusable components, documentation and engineering best practices that improve AI/ML delivery across the organisation. Collaborating with data engineers, data scientists, front & back end engineers, product managers to deliver impactful solutions. Supporting the evaluation of new AI technologies, frameworks and tooling, contributing ideas and recommendations for continuous improvement. Who you will work with Data and AI Team About you Strong Python engineering skills (FastAPI, testing, typing) and experience with cloud native development (GCP preferred). Hands on experience with GCP Vertex AI (model endpoints, pipelines, embeddings, vector search) or equivalent cloud native AI/ML platforms (e.g. AWS SageMaker, AzureML) and agent orchestration frameworks (e.g. LangChain, LangGraph, ADK). Solid understanding of MLOps - CI/CD, IaC (Terraform), experiment tracking, model registry, and monitoring. Proven experience deploying and operating ML systems in production (batch and real time). Familiarity with RAG architectures, prompt engineering, guardrails and evaluation techniques. Previous experience developing agentic capabilities, such as agent skills, MCP servers, tool usage. Strong grasp of security, privacy and governance principles (IAM, secrets, PII handling). Effective communication skills and ability to work with both technical and non technical stakeholders. An interest in evaluating new AI technologies and contributing to technical discussions around build, buy or configure decisions. Bachelor's or Master's degree in Computer Science/Engineering/related field, or demonstrable relevant experience. Additional desired skills Knowledge of vector databases and retrieval strategies. Experience with recommender systems and ranking models. Familiarity with LLM evaluation tools (e.g., RAGAS, TruLens, LangSmith, Arize). A working understanding of cloud networking and platform infrastructure. Experience in e commerce or retail environments. Why join us? Be a part of this values driven, high growth, magical journey with an ultimate vision to empower everyone, everywhere to be the best version of themselves. We're a hybrid model with flexibility, allowing you to work how best suits you. 25 days holiday (plus bank holidays) with an additional day to celebrate your birthday. Inclusive parental leave policy that supports all parents and carers throughout their parenting and caring journey. Financial security and planning with our pension and life assurance for all. Wellness and social benefits including Medicash, Employee Assist Programs and regular social connects with colleagues. Bring your furry friend to work with you on our allocated dog friendly days and spaces and not to forget our generous product discount and gifting! At Charlotte Tilbury Beauty, our mission is to empower everybody in the world to be the most beautiful version of themselves. We celebrate and support this by encouraging and hiring people with diverse backgrounds, cultures, voices, beliefs, and perspectives into our growing global workforce. By doing so, we better serve our communities, customers, employees - and the candidates that take part in our recruitment process.

Engineering Glasgow / Remote Consultant Contract We are looking for a talented and driven Senior Fullstack Backend Engineer to join our growing engineering team. In this role, you will design and build robust backend API services, integrate them with existing applications and tools, and contribute to shaping the overall system architecture. You will collaborate closely with cross functional teams following Agile practices, delivering scalable and maintainable solutions that power our AI driven products and client deployments. Key Responsibilities Design, build, and maintain high performance backend API services using Python, FastAPI, and Pandas. Develop clean, well documented RESTful and asynchronous APIs following best practices. Ensure APIs are scalable, secure, and optimized for performance in production environments. Integration with Applications & Tools Integrate backend services with existing internal and client facing applications and third party tools. Work with message brokers (RabbitMQ) to design event driven and asynchronous integration patterns. Collaborate with stakeholders to ensure seamless data flow across interconnected systems. Design, develop, and maintain background ETL processes for data ingestion, transformation, and loading. Build and optimize data pipelines that support analytics, reporting, and operational workflows. Ensure data integrity, reliability, and traceability across all pipeline stages. Contribute to and lead discussions on system architecture, ensuring solutions are robust, scalable, and maintainable. Define technical standards and patterns for backend services across the engineering team. Evaluate and recommend cloud infrastructure components on Azure and GCP to support platform needs. Manage and optimize relational data models using PostgreSQL. Deploy and manage backend services on cloud platforms, preferably Azure and/or GCP. Collaborate with DevOps/MLOps engineers on CI/CD pipelines, containerization, and deployment strategies. Monitor service health and performance, proactively addressing bottlenecks and reliability issues. Work within an Agile/Scrum team, participating in sprint planning, daily stand ups, and retrospectives. Be an active team player, supporting peers through code reviews, knowledge sharing, and pair programming. Communicate technical decisions clearly to both technical and non technical stakeholders. Education & Experience Bachelor's degree in Computer Science, Software Engineering, or a related field. 5+ years of professional experience in backend or fullstack software development. Proven experience delivering production grade backend systems at scale. Core Technical Skills Strong proficiency in Python as a primary backend language. Hands on experience with FastAPI and Pandas for building data driven API services. Solid experience with PostgreSQL - schema design, query optimization, and migrations. Experience with RabbitMQ or similar message brokers for asynchronous processing. Practical experience with cloud services, preferably Microsoft Azure and/or GCP. Demonstrated expertise in designing and implementing ETL pipelines and background processes. Strong understanding of system architecture principles - microservices, event driven design, and API gateways. Soft Skills Strong team player with excellent collaboration and interpersonal skills. Effective communicator, able to articulate complex technical concepts clearly. Self motivated, detail oriented, and capable of managing multiple priorities. Passion for writing clean, maintainable, and well tested code. Preferred Qualifications Frontend experience using React is a plus. Knowledge of SAP systems and integration patterns is advantageous. Familiarity with LLMs and AI/ML integration patterns is a plus but not mandatory. Experience working in cross functional, remote, or distributed engineering teams. Exposure to containerization of Applications (Docker, Kubernetes). What We Offer Competitive consultancy fee commensurate with experience. Collaborative and growth oriented work environment. Continuous learning opportunities and access to cutting edge AI technologies. If this sounds like you, we'd love to hear from you. Join the enterprises scaling their autonomous workflows with Kodamai's next generation framework.

Job Overview We are looking for a Senior ML Engineer to take technical ownership of our machine learning production environment. You will lead the transition of experimental models into production-grade services that are reliable, scalable, and cost-effective. Your mission is to build the "highway" that allows our data science team to deploy models rapidly while ensuring those models are observable and fiscally responsible. You will own the entire ML lifecycle-from automated training pipelines to real-time inference clusters-and serve as a key software engineering contributor to our AI product stack. This is a hybrid role - three days per week in our Newcastle office. Key Responsibilities Lifecycle & Pipeline Architecture: Design and own the automated "Continuous Training" (CT) and deployment pipelines. Architect reusable, modular infrastructure for model training and serving, ensuring the entire lifecycle is versioned and reproducible. Software Engineering Best Practices: Lead the team in adopting professional engineering standards. Own the strategy for unit/integration testing, peer code reviews, and apply SOLID principles to ML codebases to ensure they remain modular and maintainable. ML Observability: Establish and own the telemetry framework for the AI stack. Implement proactive monitoring for system health and model-specific metrics, such as data drift, concept drift, and prediction accuracy. FinOps & Cost Management: Own the strategy for AI cloud spend. Build monitoring and alerting frameworks to track compute costs (training and inference) and implement optimization strategies like auto scaling and spot instance usage. AI Systems Engineering: Act as a lead software engineer to integrate models into the product ecosystem. Develop high performance, secure APIs and microservices that wrap our ML capabilities for production consumption. Data & Model Governance: Own the versioning strategy for the "Holy Trinity" of ML: code, data, and model artifacts. Ensure clear documentation and audit trails for all production deployments. Essential Skills (Entry Requirements) Demonstrating strong software engineering fundamentals, including production quality Python, testing, CI/CD practices, and version control. Designing and operating reliable, versioned REST APIs using an API first approach. Building, deploying, and operating backend services in cloud environments, with AWS as the primary platform (experience on other major clouds considered transferable). Using containerisation and modern deployment approaches, including Docker, automated pipelines, and basic observability. Working effectively with real world data and production systems in collaboration with product, data, and platform teams. Bringing either hands on experience delivering machine-learning systems in production or a very strong software engineering background with clear motivation to grow into ML and MLOps. Additional Experience & Capabilities Using AWS SageMaker for training, deploying, and operating machine-learning workloads, or demonstrating equivalent experience on similar cloud ML platforms. Exposing machine-learning models via APIs (e.g. FastAPI based inference services) and operating them reliably at scale. Applying MLOps practices, including model and version management, monitoring, and handling model or data drift. Implementing advanced service patterns such as asynchronous processing, event driven architectures, or multi-version services. Serving LLM or GenAI-based capabilities in production, including model serving, RAG pipelines, and inference controls. Designing reusable, platform-level services and shared ML patterns rather than one off implementations. Managing cloud operational trade-offs, including cost efficiency, latency, scalability, and reliability.

Job Overview We are looking for a Senior ML Engineer to take technical ownership of our machine learning production environment. You will lead the transition of experimental models into production-grade services that are reliable, scalable, and cost-effective. Your mission is to build the "highway" that allows our data science team to deploy models rapidly while ensuring those models are observable and fiscally responsible. You will own the entire ML lifecycle-from automated training pipelines to real-time inference clusters-and serve as a key software engineering contributor to our AI product stack. This is a hybrid role - three days per week in our Newcastle office. Key Responsibilities Lifecycle & Pipeline Architecture: Design and own the automated "Continuous Training" (CT) and deployment pipelines. Architect reusable, modular infrastructure for model training and serving, ensuring the entire lifecycle is versioned and reproducible. Software Engineering Best Practices: Lead the team in adopting professional engineering standards. Own the strategy for unit/integration testing, peer code reviews, and apply SOLID principles to ML codebases to ensure they remain modular and maintainable. ML Observability: Establish and own the telemetry framework for the AI stack. Implement proactive monitoring for system health and model-specific metrics, such as data drift, concept drift, and prediction accuracy. FinOps & Cost Management: Own the strategy for AI cloud spend. Build monitoring and alerting frameworks to track compute costs (training and inference) and implement optimization strategies like auto scaling and spot instance usage. AI Systems Engineering: Act as a lead software engineer to integrate models into the product ecosystem. Develop high performance, secure APIs and microservices that wrap our ML capabilities for production consumption. Data & Model Governance: Own the versioning strategy for the "Holy Trinity" of ML: code, data, and model artifacts. Ensure clear documentation and audit trails for all production deployments. Essential Skills (Entry Requirements) Demonstrating strong software engineering fundamentals, including production quality Python, testing, CI/CD practices, and version control. Designing and operating reliable, versioned REST APIs using an API first approach. Building, deploying, and operating backend services in cloud environments, with AWS as the primary platform (experience on other major clouds considered transferable). Using containerisation and modern deployment approaches, including Docker, automated pipelines, and basic observability. Working effectively with real world data and production systems in collaboration with product, data, and platform teams. Bringing either hands on experience delivering machine-learning systems in production or a very strong software engineering background with clear motivation to grow into ML and MLOps. Additional Experience & Capabilities Using AWS SageMaker for training, deploying, and operating machine-learning workloads, or demonstrating equivalent experience on similar cloud ML platforms. Exposing machine-learning models via APIs (e.g. FastAPI based inference services) and operating them reliably at scale. Applying MLOps practices, including model and version management, monitoring, and handling model or data drift. Implementing advanced service patterns such as asynchronous processing, event driven architectures, or multi-version services. Serving LLM or GenAI-based capabilities in production, including model serving, RAG pipelines, and inference controls. Designing reusable, platform-level services and shared ML patterns rather than one off implementations. Managing cloud operational trade-offs, including cost efficiency, latency, scalability, and reliability.

Engineering Glasgow / Remote Consultant Contract We are looking for a talented and driven Senior Fullstack Backend Engineer to join our growing engineering team. In this role, you will design and build robust backend API services, integrate them with existing applications and tools, and contribute to shaping the overall system architecture. You will collaborate closely with cross functional teams following Agile practices, delivering scalable and maintainable solutions that power our AI driven products and client deployments. Key Responsibilities Design, build, and maintain high performance backend API services using Python, FastAPI, and Pandas. Develop clean, well documented RESTful and asynchronous APIs following best practices. Ensure APIs are scalable, secure, and optimized for performance in production environments. Integration with Applications & Tools Integrate backend services with existing internal and client facing applications and third party tools. Work with message brokers (RabbitMQ) to design event driven and asynchronous integration patterns. Collaborate with stakeholders to ensure seamless data flow across interconnected systems. Design, develop, and maintain background ETL processes for data ingestion, transformation, and loading. Build and optimize data pipelines that support analytics, reporting, and operational workflows. Ensure data integrity, reliability, and traceability across all pipeline stages. Contribute to and lead discussions on system architecture, ensuring solutions are robust, scalable, and maintainable. Define technical standards and patterns for backend services across the engineering team. Evaluate and recommend cloud infrastructure components on Azure and GCP to support platform needs. Manage and optimize relational data models using PostgreSQL. Deploy and manage backend services on cloud platforms, preferably Azure and/or GCP. Collaborate with DevOps/MLOps engineers on CI/CD pipelines, containerization, and deployment strategies. Monitor service health and performance, proactively addressing bottlenecks and reliability issues. Work within an Agile/Scrum team, participating in sprint planning, daily stand ups, and retrospectives. Be an active team player, supporting peers through code reviews, knowledge sharing, and pair programming. Communicate technical decisions clearly to both technical and non technical stakeholders. Education & Experience Bachelor's degree in Computer Science, Software Engineering, or a related field. 5+ years of professional experience in backend or fullstack software development. Proven experience delivering production grade backend systems at scale. Core Technical Skills Strong proficiency in Python as a primary backend language. Hands on experience with FastAPI and Pandas for building data driven API services. Solid experience with PostgreSQL - schema design, query optimization, and migrations. Experience with RabbitMQ or similar message brokers for asynchronous processing. Practical experience with cloud services, preferably Microsoft Azure and/or GCP. Demonstrated expertise in designing and implementing ETL pipelines and background processes. Strong understanding of system architecture principles - microservices, event driven design, and API gateways. Soft Skills Strong team player with excellent collaboration and interpersonal skills. Effective communicator, able to articulate complex technical concepts clearly. Self motivated, detail oriented, and capable of managing multiple priorities. Passion for writing clean, maintainable, and well tested code. Preferred Qualifications Frontend experience using React is a plus. Knowledge of SAP systems and integration patterns is advantageous. Familiarity with LLMs and AI/ML integration patterns is a plus but not mandatory. Experience working in cross functional, remote, or distributed engineering teams. Exposure to containerization of Applications (Docker, Kubernetes). What We Offer Competitive consultancy fee commensurate with experience. Collaborative and growth oriented work environment. Continuous learning opportunities and access to cutting edge AI technologies. If this sounds like you, we'd love to hear from you. Join the enterprises scaling their autonomous workflows with Kodamai's next generation framework.

Overview Blackstone is the world's largest alternative asset manager, managing $1.1 trillion in assets across multiple investment vehicles. The Blackstone Technology & Innovations (BXTI) team builds systems to support risk management, efficiency, and transparency across the firm and its portfolio companies. Job Summary AVP - Liquid Credit Technology. The Liquid Credit Technology team develops modern fixed income asset management systems (portfolio, order, execution, trade processing) to support LCS, which manages $114B in AUM across diverse fixed income portfolios. Key Technologies C#, React/Angular, Typescript, FastAPI, Python, Terraform, SQL, AWS ECS, AWS Lambda, AWS DynamoDB, AWS SNS/SQS, CI/CD (GitLab Runners), Snowflake. Responsibilities Use cloud native technologies and services to build scalable, reliable, and secure applications. Build, support, and integrate web applications, microservices, and data pipelines with high code quality. Write automated unit, integration, and deployment tests. Use CI/CD tooling (e.g., GitLab Runners) to build and deploy code across environments. Apply modern development methodologies; use JIRA for project tracking. Participate in technical design, code reviews, and agile ceremonies; troubleshoot defects. Provide technical support, automate repetitive tasks, stay updated with industry trends. Mentor and train junior developers; contribute to a collaborative team culture. Potential requirement for securities licenses if client facing responsibilities arise. Qualifications At least 3years of proven software development experience in relevant industry. Proficiency in C#, JavaScript (React and/or Angular), Typescript, relational/NoSQL databases, and cloud technologies (preferably AWS). Experience designing, developing, and operating scalable microservice architectures and RESTful APIs. Strong object oriented programming background and ability to develop secure, maintainable code. Excellent problem solving, communication, and teamwork skills. Self starter with entrepreneurial attitude, willingness to mentor, and thrive in fast paced environments. Experience with automation testing and performance testing. Fixed income front office trading systems experience preferred. Bachelor's degree in Computer Science, Engineering, or related field. Equal Opportunity Employer Blackstone is committed to providing equal employment opportunities to all employees and applicants for employment without regard to race, color, creed, religion, sex, pregnancy, national origin, ancestry, citizenship status, age, marital or partnership status, sexual orientation, gender identity or expression, disability, genetic predisposition, veteran or military status, status as a victim of domestic violence, a sex offense or stalking, or any other class or status in accordance with applicable federal, state and local laws. This policy applies to all terms and conditions of employment, including but not limited to hiring, placement, promotion, termination, transfer, leave of absence, compensation, and training.