BLOOMBERG

Bloomberg is seeking a Product Security Engineer to ensure software is built securely. The successful candidate will develop automated security capabilities across the software development lifecycle and collaborate with engineering teams to enhance security testing. Key qualifications include 3+ years of software development experience and strong skills in DevOps tools like GitHub and Jenkins. Knowledge in AI-assisted security workflows and OWASP vulnerabilities is essential.

Bloomberg is seeking a Technical Product Manager for the Agentic Infrastructure within its CTO Office. This role requires 5+ years in technical product management, focusing on AI and infrastructure. You will define and execute strategies for scalable and secure AI systems while collaborating across engineering, product, and security teams. Your expertise in AI platforms and cloud infrastructure will contribute to shaping Bloomberg's AI future, ensuring reliable governance and deployment. Join us to impact how agentic systems operate at an enterprise scale.

Product Security Engineer - Software Security Enablement Location London Business Area Legal, Compliance, and Risk Ref # Description & Requirements Our Team: Bloomberg is building the world's most trusted information network for financial professionals. We protect Bloomberg. We partner with internal departments to ensure the confidentiality, integrity, and availability of Bloomberg systems and the data we process. We aim to ensure that our clients see us as a trusted partner. Our Chief Information Security Office (CISO) owns the technical aspects of this mission by ensuring Bloomberg products, systems, networks and commercial applications are built and maintained with security in mind. What's the role? We are seeking a Product Security Engineer to help ensure that Bloomberg software is built securely. You will be responsible for building and maintaining automated security capabilities across the software development lifecycle. You will also engage with engineering partners to provide remediation guidance and enhance security testing to deliver high fidelity, actionable results. As a member of the Product Security Enablement team, you will help provide automated security testing solutions for Bloomberg, including SAST, DAST, SCA, Secret searching and LLM based assessments. Our team's goal is to create preventative security capabilities that integrate into development pipelines and help detect issues early in the software development lifecycle. An engineering skillset is required for this role. You will be responsible for prototyping new tools, integrating security testing tools and capabilities into the software development lifecycle, and developing custom security capabilities to deliver scalable testing solutions to our engineering teams. This role will routinely challenge your technical background and critical thinking. You will be expected to collaborate with different stakeholders in a fast paced environment across many technology stacks and services. We'll trust you to: Partner with engineering stakeholders to understand Bloomberg's development landscape and security needs. Develop automated security solutions that integrate into development pipelines. Maintain and enhance existing security automation processes and security capabilities. Understand and research technical details of core technology stacks and develop or enhance custom code analysis queries. Communicate vulnerability landscape and work on mitigations with stakeholders across the business. Actively monitor the latest news and trends in automated security capabilities, secure development, and AI assisted security workflows. Develop and enhance operational runbooks. Perform ad hoc vulnerability discovery, including code review and static analysis for key engineering teams, applications and services. Build or adopt new security capabilities to address issues at scale, such as Software Composition Analysis, Secret searching, and other automated security testing techniques. Use LLMs and AI assisted workflows as part of security assessments, vulnerability research, secure code review, developer enablement, and security automation. Explore, evaluate, and build automation using modern LLM tooling and integration patterns, including custom skills, MCP servers, agentic workflows, retrieval augmented workflows, and integrations with development and security tooling. You'll need to have: A strong core engineering background with a proven track record. 3+ years of experience in software development. Knowledge and experience with DevOps and software used in development pipelines (e.g. Github, Jenkins). Working knowledge of build systems, package managers, and development tooling (such as cmake, npm, maven, gradle etc). A core understanding of common security vulnerabilities, such as OWASP Top 10 issues and language specific vulnerabilities. Experience using, evaluating, or building with LLMs or AI assisted tooling in technical workflows. Ability to combine technical knowledge with an understanding of core aspects of an information security program. Motivation to keep up with latest trends and techniques in the information security community. Excellent written and verbal communication skills. We'd love to see (not required, but nice to have!): Experience or familiarity with running, maintaining, and customizing static analysis security testing tools such as CodeQL and Semgrep. Experience using LLMs or AI assisted tools for security assessments, vulnerability research, secure code review, developer enablement, or security automation. Familiarity with LLM automation concepts and tooling, such as custom skills, MCP servers, agentic workflows, retrieval augmented workflows, or integrations with development and security tooling. Knowledge of open source software component management, Software Composition Analysis, and related security tools. Knowledge of core concepts in public cloud providers such as AWS, GCP, and Azure. Familiarity with container orchestration technologies such as Kubernetes and Docker, and cloud deployment orchestration. Technical information security certifications, such as CISSP, CSSLP, or SANS certifications. Prior experience integrating security testing into DevOps pipelines.

Technical Product Manager - GenAI Platforms - Agentic Infrastructure - CTO Office Location: London Business Area: Engineering and CTO Ref #: Description & Requirements Bloomberg's CTO Office is the future looking technical and product arm of Bloomberg L.P. We envision, design, and prototype the next generation of infrastructure, hardware, and applications that power the Bloomberg Terminal and beyond. Our work spans AI platforms, cloud infrastructure, open source stewardship, and generative AI innovation. For over a decade, Bloomberg has been at the forefront of applying AI, ML, and NLP to financial intelligence, powering products in sentiment analysis, classification, document understanding, recommendation, and generative AI. Critical to this effort are our AI platforms, which enable teams to rapidly and robustly build, deploy, evaluate, govern, and operate AI systems at scale. As Bloomberg expands its investment in Generative and Agentic AI, we are building the trustworthy infrastructure that will power the next generation of intelligent products across Terminal, Enterprise, and client facing experiences. What's In It For You We are looking for a Technical Product Manager to define and execute the strategy for our Agentic Infrastructure, the connective tissue and foundational layer that enables AI agents, tools, and applications to operate safely, securely, and at scale across Bloomberg. This role sits at the intersection of our AI Platforms, cloud infrastructure, security, and distributed systems. You will shape the capabilities that govern how AI systems authenticate, communicate, access resources, execute actions, and interact with Bloomberg infrastructure, ensuring that as we scale agentic systems, we do so with trust, reliability, and enterprise grade governance by design. You will partner closely with Engineering, Product, Security, CTO, and Risk stakeholders to build an interoperable control plane, establishing a trustworthy foundation for the next generation of AI powered products. Why This Matters Agentic systems introduce new infrastructure challenges beyond traditional software and machine learning platforms. As AI systems become capable of autonomous action, tool use, multi agent collaboration, and long running workflows, organizations require new infrastructure for identity, authorization, execution environments, networking, governance, observability, and lifecycle management. We'll trust you to Define and drive the vision for Bloomberg's Agentic Infrastructure, with a focus on agentic control planes Translate emerging open source & industry standards into production ready, enterprise grade infrastructure capabilities Collaborate across Bloomberg's AI platform teams to integrate agentic capabilities that support experimentation and production deployment Develop platform strategies for agentic identity, access control, sandboxing, network, and connectivity architecture Work directly with AI product teams to understand real world usage and ensure infrastructure solutions support and advance the AI application lifecycle Partner deeply with engineering to deliver scalable, resilient system architecture Anticipate how agentic systems will evolve, and proactively shape the roadmap to support future capabilities You'll Need to Have 5+ years of experience in technical product management, ideally within AI, platform, cloud, security, or infrastructure domains Experience working with AI or GenAI systems, with LLMs, generative AI, agent frameworks and orchestration systems, and their production requirements Experience building or operating large scale platform infrastructure used by internal or external developers Strong understanding of identity, authentication/authorization, enterprise security architectures Strong understanding of distributed systems, service to service communication, API Gateways, Kubernetes, cloud native architectures Hands on experience working with emerging agentic protocols (MCP, A2A) and interoperability patterns Proven ability to work cross functionally with engineering, security, product, and platform organizations Excellent communication and storytelling skills, with the ability to articulate a technical vision and influence across diverse teams We'd Love to See A degree in Computer Science, Engineering, or prior equivalent architecture experience Experience building control planes, policy engines, governance frameworks Exposure to enterprise governance, compliance, or regulated environments Contributions to open source or developer ecosystems Why Join Us You will play a pivotal role in shaping Bloomberg's AI future by building the infrastructure foundations that enable trusted, scalable, and production ready AI systems. This is an opportunity to help define how agentic systems operate at enterprise scale, influencing platform strategy across identity, security, networking, governance, cloud infrastructure, and interoperability. You will work alongside world class engineers, architects, researchers, and product leaders while helping establish the trusted infrastructure foundation that powers Bloomberg's next generation of AI innovation. If indicated, please note that years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role.

Bloomberg is looking for a Product Manager in London to manage quantitative data solutions. This role requires expertise in research data and a comprehensive understanding of capital markets. The ideal candidate will bring at least 5 years of relevant experience, a strong proficiency in Python or similar programming, problem-solving skills, and a collaborative mindset. A bachelor's degree in statistics or a related field is necessary. This position offers the opportunity to lead product development in an innovative environment dedicated to excellence in data solutions.

Bloomberg is seeking a Product Manager - Data User Experience - BQuant in London. You will define and execute the vision for core data and analytics, enhancing user interactions with Bloomberg's extensive financial data. The role requires strong experience in product strategy and collaboration with engineering teams, focusing on delivering complex solutions that integrate various data types effectively. Candidates with 5+ years of relevant expertise are encouraged to apply.

Product Manager - Data User Experience - BQuant Location London Business Area Engineering and CTO Ref # Description & Requirements What we do Bloomberg is the global leader in financial data, analytics, and technology. Our products power the workflows of financial professionals across research, trading, portfolio management, and risk. At the centre of this is BQuant. BQuant reimagines the Bloomberg experience by putting code at its core - it brings together the cutting edge of our Data, API, and AI strategies to enable unprecedented customization and time-to-value for our code-aware users, and in a manner that is instantly available. These users can quickly analyze and combine Bloomberg's extensive financial data and analytics with their own, to build models and workflows that span the entire investment lifecycle, and easily make these available to any other user at their firm. Your Role As Product Lead for the Data User Experience, you will define and drive the vision, strategy, and execution of the core data and analytics experience within BQuant. You will be responsible for how users discover, access, understand, and work with data, enabling them to combine Bloomberg data with proprietary datasets to power research, trading and AI applications - with confidence and trust. Your customers will include both end users and internal teams building workflow specific solutions on top of the platform, such as backtesting and trading systems integrations. You will also serve as the primary liaison to Bloomberg's data producing teams, and will work closely with Engineering, Quants, and other product managers to ensure the platform enables a wide range of use cases, from exploratory research to production grade applications. What You'll Do Define the Data User Experience Set the vision and own the execution for the end to end data experience in BQuant Own the roadmap and backlog, taking into account external and internal customer input, product strategy, value propositions, competitor analysis and operational requirements Balance short term improvements with long term platform scalability Build a Scalable Data Analytics Platform Ensure data can be easily integrated, enriched, and combined with client data Define and evolve API abstractions for using financial and alternative datasets Ensure data is provisioned with appropriate SLAs, reliability, and performance Enable support for different workflows using batch and streaming data Drive consistency in how data is modeled, accessed, and used across the platform Ensure robust handling of entitlements, security, and data governance Enable Quantitative and Data Intensive Workflows Support workflows across research, backtesting, and production deployment Enable users to generate signals and analytics from combined datasets Partner with teams building solutions on top of the data platform Ensure the platform supports multi asset and complex financial data use cases Enable users to trust data across the full lifecycle from experimentation to production Act as the primary liaison with data producing teams to onboard new datasets Partner with Engineering, UX, and other product teams to deliver cohesive solutions Balance the needs of internal platform users and external clients What We're Looking For Proven ability (5 yrs+) to define and execute product strategy for platform products Expert prioritization skills balancing user needs, technical constraints, and business impact Experience delivering complex products from concept through execution Data Platform Expertise and Innovation Strong experience building or leading data platforms or analytics infrastructure Good understanding of data access patterns, APIs, and data modeling Experience working with large scale datasets, including time series and streaming data Practical experience applying AI/ML to solve customer problems, with a strong understanding of how to translate emerging capabilities into product strategy and measurable outcomes Partnership & Communication Deep experience working closely with engineering teams on technical platform products Excellent communication skills with both technical and non technical stakeholders Strong collaboration skills across Product, Engineering, Quants, and business teams Quantitative & Data Workflow Understanding Understanding of workflows across research, analytics, and trading Experience enabling users to combine multiple datasets and generate insights Familiarity with challenges in moving from research to production systems Experience addressing data quality, entitlements, security, and governance challenges If indicated, please note that years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role. Discover what makes Bloomberg unique - watch our podcast series for an inside look at our culture, values, and the people behind our success.

Bloomberg is seeking a Technical Product Manager for Data Manufacturing Infrastructure in London. This role requires 8+ years of experience in technical product management, focusing on data pipelines and infrastructure optimization. You will collaborate with engineering and data management teams to shape the roadmap, balancing complex infrastructure needs with operational objectives. A strong technical background in distributed systems and product design, along with excellent communication skills, is essential.

Technical Product Manager - Data Manufacturing Infrastructure Location London Business Area Data Ref # Description & Requirements Bloomberg runs on data. In Data, we are transforming how that data is manufactured, observed, validated, and prepared for use by clients, internal systems, and AI-driven products. Our data manufacturing infrastructure supports the pipelines that move content from acquisition through classification, validation, enrichment, modeling, and publication. As those workflows become more automated and AI-enabled, we need infrastructure that is observable, measurable, resilient, and designed for continuous improvement. Data Management & Operations (DMO) is looking for a Technical Product Manager to help shape the next generation of data manufacturing infrastructure. This role will partner closely with DMO, partner Engineering Infrastructure, AI, and domain teams to define a product roadmap for infrastructure capabilities that support automation, observability, process analysis, semantic data readiness, and scalable production workflows. This is not a traditional project management role. You will apply product discipline to infrastructure: translating complex methodological, operational, and Engineering needs into a clear and articulate roadmap; helping teams make explicit tradeoffs; and ensuring that infrastructure design decisions support the long term strategy for data manufacturing optimization and automation. We'll trust you to: Define and maintain the product roadmap for data manufacturing infrastructure in partnership with DMO and Engineering leadership, ensuring priorities are clear, defensible, and aligned to Data's goals and strategy. Prioritize needs across multiple stakeholders to construct a coherent backlog that reduces complexity and achieves focus. Balance competing infrastructure needs, including observability, pipeline analysis, and technical migrations. Possess a robust knowledge of data manufacturing approaches across Data, and develop strategies that improve adoption while respecting Engineering architecture and operational constraints. Evaluate where agentic and LLM-based approaches add value in the data manufacturing pipeline, and where deterministic microservices, rules engines, APIs, or other traditional implementations remain the better solution. Partner with Engineering on new pipeline components to ensure added intelligence does not reduce observability, diagnosability, maintainability, or operational resilience. Maintain a clear view of technological trends and evaluate open source or third party software that may support the data manufacturing process. Help ensure the observability platform evolves beyond technical event monitoring into an operational intelligence layer that supports analysis, experimentation, simulation, and continuous improvement. Develop a structured interface between Engineering and internal stakeholders, structuring conversations to be well scoped, technically grounded, and actionable. Shape inbound demand to Engineering, helping stakeholders articulate needs in a way that is complete, prioritized, and consistent with the platform direction. Communicate the Engineering roadmap and platform capabilities to DMO, AI, and domain teams so they can plan their own work with greater confidence. Drive incremental, reversible delivery. You will help define maintainability criteria, release gates, and post-incident learning loops so that edge cases and failures are fed back into product requirements. You'll need to have: Please note we use years of experience as a guide, but we certainly will consider applications from all candidates who are able to demonstrate the skills necessary for the role. 8+ years of experience, including substantial experience in technical product management for infrastructure, platform, data pipeline, or production scale systems. Experience building product management practice in environments where it did not previously exist, including earning credibility with senior engineers before exercising influence. Technical fluency across microservices architecture, distributed systems, APIs, data pipelines, and platform design. Experience translating ambiguous business, operational, or analytical needs into clear product requirements and Engineering ready specifications. Experience defining observability, telemetry, or operational intelligence requirements as part of product design, not only as post deployment monitoring. Strong judgment about when to use AI, LLM, or agentic approaches and when simpler deterministic designs are more appropriate. Strong written communication skills, including the ability to produce clear product requirements, decision memos, roadmap narratives, and senior leadership updates. Proven ability to lead through influence across cross functional or matrixed teams where formal authority is limited or absent. A track record of building trust with technical teams through partnership, clarity, and disciplined prioritization. We'd love to see: Experience with data platforms, ETL/ELT systems, data contracts, schema governance, data quality tooling, metadata management, or lineage platforms. Familiarity with process analytics, statistical process control, workflow simulation, experimentation, or other methods used to evaluate operational systems. Experience defining infrastructure or data product requirements for AI and LLM consumption, including structured and unstructured content workflows. Exposure to data observability tools, lineage systems, or operational monitoring platforms, including a point of view on where these tools succeed and where they fall short. Experience working with semantic models, knowledge graphs, entity resolution, metadata governance, or AI ready data initiatives. Academic or professional background in computer science, data engineering, statistics, economics, operations research, or a related technical discipline. You'll be successful in this role if you: Improve the velocity and variety of content that is ingested by Data and converted into robust data products. Improve the Data's ability to adopt relevant, emerging technologies, as well as pivot to new or differently structured data products. Build credibility with engineering by demonstrating technical depth, judgment, and respect for architectural ownership. Help DMO, Engineering, AI, and domain teams converge on a shared roadmap for data manufacturing infrastructure. Turn observability and instrumentation from a monitoring function into a product capability that supports better decisions. Make infrastructure priorities more visible, adoption paths clearer, and tradeoffs easier for senior stakeholders to understand. Improve the organization's ability to evaluate automation opportunities empirically rather than relying on intuition, one off analyses, or disconnected tooling.

Bloomberg is looking for a Senior Data Management Professional in London to enhance data governance and operationalize quality standards. This role involves shaping governance policies and frameworks that align with regulatory expectations while promoting best practices across teams. The ideal candidate will have over 4 years in data management and governance, strong SQL skills, and experience with data visualization tools. Join Bloomberg to help ensure the integrity and quality of our data offerings.

Senior Data Management Professional - Data Governance - Semantic Integrations Location London Business Area Data Ref # Description & Requirements Bloomberg runs on data. Our products are fueled by powerful information. We combine data and context to paint a complete picture for our clients-around the clock and around the world. In Data, we are responsible for delivering this data, news, and analytics through innovative technology-quickly and accurately. We apply product thinking, domain expertise, and technical insight to continuously improve our data offerings, ensuring they remain reliable, scalable, and fit for purpose in a fast changing landscape. The Role: This role sits in Semantic Integrations, part of our Knowledge Graph Group. You will define "what good looks like." You will move beyond high level policy to define the concrete standards, naming conventions, and architectural blueprints that govern platforms by setting up an enterprise wide governance framework and best practices across Data, Product, and Engineering. You will operate as a bridge between strategy and execution-ensuring that our Data is built upon a foundation of rigorous data quality, clear ownership, and consistent engineering practices. As a Senior Data Management Professional, you will be responsible for shaping, implementing, and operationalizing metadata our clients rely on. You will act as a proactive specialist by setting the strategy in achieving quality and consistency, and delivering scalable governance across Bloomberg Data. Beyond governing data and being problem solvers, they are expected to transform the responsibilities of the team and scale the impact beyond what's possible today. We'll trust you to: Define & Evolve Governance Standards: Author, maintain, and evolve governance policies, minimum requirements, and best practice standards. Ensure alignment with regulatory expectations (e.g., DORA, GDPR) and internal risk posture while keeping guidance practical and usable. Operationalize Governance in Delivery: Embed governance practices into product development, data lifecycle management, and engineering workflows. Partner with teams to pilot governance approaches and adapt them based on real world feedback. Drive Cross Domain Alignment: Act as a point of coordination across Data, Product, and Engineering for governance related topics. Resolve ambiguity around ownership, accountability, and standards through structured discussions and documented outcomes. Govern Shared Definitions & Semantics: Own the governance of shared vocabularies, taxonomies, and glossary standards. Facilitate agreement on critical business definitions and ensure consistency across platforms and domains. Measure Adoption, Maturity & Risk: Define meaningful metrics to assess governance adoption, maturity, and risk exposure. Report insights to stakeholders, focusing on outcomes such as compliance readiness, consistency, and decision quality. Facilitate Governance Forums & Working Groups: Plan and run governance working sessions, reviews, and decision forums. Prepare materials, drive consensus, and ensure decisions are clearly captured and communicated. Enable Best Practice Adoption: Develop playbooks, templates, and starter packs that support self service adoption of governance standards. Continuously refine guidance to reflect changing business needs and lessons learned. Champion Governance Culture: Promote governance literacy through training, communication, and hands on support. Act as a trusted advisor to teams navigating governance, quality, or ownership challenges. You'll need to have: Please note we use years of experience as a guide, but we certainly will consider applications from all candidates who are able to demonstrate the skills necessary for the role. Bachelor's degree in Business, Information Management, Computer Science, Law, or a related field. Solid understanding of regulatory and risk drivers (e.g., GDPR, BCBS 239, DORA) and how they translate into operational practices. 4+ years of experience in governance, data management, risk, compliance, or closely related disciplines. Demonstrated experience operating independently on complex, ambiguous governance problems. Strong working knowledge of governance and maturity frameworks. Proven ability to influence senior stakeholders and drive alignment without direct authority. Experience working with governance, metadata, or knowledge management tools (vendor agnostic). Deep understanding and experience in Master Data Management (MDM) or Market Data Security Master Management Project management skills with the ability to prioritize and adapt to tasks accordingly Proficiency in SQL for data querying and manipulation. Experience with data visualization tools (e.g., Qlik, Tableau, Power BI) and advanced Excel functionality. Familiarity with scripting languages (e.g., Python) for data analysis and automation. We'd love to see: Experience establishing or significantly scaling governance practices in a complex organization. Exposure to metadata systems, data modeling, semantic technologies, linked data and/or knowledge graphs. Background in regulated or highly data driven environments (financial services, data providers, platforms). Evidence of mentoring, facilitation, or informal leadership in cross functional settings. Understanding of Data Governance and Data Management, supported by industry certifications (e.g. DAMA CDMP, DCAM, etc.) Experience with collaborative design platforms, such as MIRO and FIGMA. Experience working in agile environments. Does this sound like you? Apply if you think we're a good match! We'll get in touch to let you know what the next steps are. If indicated, please note that years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role. Discover what makes Bloomberg unique - watch our podcast series for an inside look at our culture, values, and the people behind our success.

Software Integration Engineer - Bloomberg Broadway Location London Business Area Product Ref # Description & Requirements Bloomberg Broadway builds and delivers high-performance distributed systems that streamline the trading and transacting of money and financial assets. Our platform empowers clients to compose, adapt, and scale intelligent systems for Fixed Income markets with a level of configurability and control that was previously impossible. Our Software Integration Engineers are solution architects and technical engagement leads who collaborate directly with clients to deliver customized workflows and integrations. While coding may be part of the role, it is not the core focus - domain expertise and systems and integration engineering are what drive success. As a Software Integration Engineer, we'll expect you to: Design and deploy custom workflows across critically important, latency-sensitive distributed trading platforms. Configure and integrate Broadway's flexible components to meet nuanced client needs. Act as a domain-focused product owner, defining and shaping incremental delivery pieces through "Micro Product Management." Engage deeply with front-office users and technologists - from traders and quants to IT and business leads - to understand workflows and translate them into actionable designs. Own delivery end-to-end, managing requirements, timelines, and solution quality across stakeholder groups. Contribute to ongoing system evolution by surfacing client use cases that inform product design and integration patterns. When needed, extend functionality through light programming (in Python, Java, C++, or C#). This is not a heads-down coding job. This is a high-impact integration role for engineers who want to own solutions, talk to clients, and shape systems that get used. You'll operate at the center of business logic, architecture, and client delivery-where technology meets the market. You'll need to have: 5+ years of experience in software engineering, systems integration or solution architecture in complex enterprise environments. Strong understanding of distributed systems principles and how to troubleshoot, configure, and optimize large-scale services. Experience in real-time or high-throughput system environments-preferably in capital markets or a similarly time-sensitive domain. Excellent communication skills: you can explain, persuade, and guide both technical and non-technical audiences. Familiarity with databases (SQL) and scripting languages to support integration and customization work. An advanced degree in Computer Science, Engineering, Mathematics, or equivalent hands-on experience. Experience collaborating directly with customers to deliver software-either through integration or development. We'd love to see: Front-office trading or capital markets exposure, especially in Fixed Income. Proven ability to turn business objectives into system designs and integration plans. Curiosity and depth-willingness to push past surface-level requirements to design robust, scalable solutions. Self-direction and ownership in navigating people, process, and technology. A collaborative mindset-sharing insights, building on others' work, and elevating team capabilities. If indicated, please note that years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role.

Bloomberg is looking for a Software Integration Engineer to design and deploy custom workflows for critical trading platforms. You will engage with clients and technical teams to shape integrated solutions. The ideal candidate has over 5 years of experience in software engineering with strong communication skills. This position emphasizes both technical expertise and client interaction, ensuring that solutions align with business needs.

A leading financial technology firm in Greater London is seeking a Senior GenAI Platform Engineer to architect and build multi-tenant GenAI platform systems. This role requires strong programming skills (Python, Go), experience with GenAI technologies, and a degree in a related field. You will work closely with application teams to optimize workflows and collaborate with open-source communities for enhanced development experiences. Join us to contribute to innovative AI-driven financial solutions.

Location London Business Area Engineering and CTO Ref # Description & Requirements Bloomberg's Engineering AI department has 400+ AI practitioners building highly sought after products and features that often require novel innovations. We are investing in AI to build better search, discovery, and workflow solutions using technologies such as transformers, gradient boosted decision trees, large language models, and dense vector databases. We are expanding our group and seeking highly skilled individuals who will be responsible for contributing to the team (or teams) of Machine Learning (ML) and Software Engineers that are bringing innovative solutions to AI-driven customer-facing products. At Bloomberg, we believe in fostering a transparent and efficient financial marketplace. Our business is built on technology that makes news, research, financial data, and analytics on over 35 million financial instruments searchable, discoverable, and actionable across the global capital markets. Bloomberg has been building Artificial Intelligence applications that offer solutions to these problems with high accuracy and low latency since 2009. We build AI systems to help process and organize the ever-increasing volume of structured and unstructured information needed to make informed decisions. Our use of AI uncovers signals, helps us produce analytics about financial instruments in all asset classes, and delivers clarity when our clients need it most. We are looking for Senior GenAI Platform Engineers with strong expertise and passion for building platforms, especially for GenAI systems. As a Senior GenAI Platform Engineer, you will have the opportunity to create a more cohesive, integrated, and managed GenAI development life cycle to enable the building and maintenance of our ML systems. Our teams make extensive use of open source technologies such as Kubernetes, KServe, MCP, Envoy AI Gateway, Buildpacks and other cloud-native and GenAI technologies. From technical governance to upstream collaboration, we are committed to enhancing the impact and sustainability of open source. Join the AI Group as a Senior GenAI Platform Engineer and you will have the opportunity to: Architect, build, and diagnose multi-tenant GenAI platform systems Work closely with GenAI application teams to design seamless workflows for continuous model training, inference, and monitoring Interface with both GenAI experts to understand workflows, pinpoint and resolve inefficiencies, and inform the next set of features for the platforms Collaborate with open-source communities and GenAI application teams to build a cohesive development experience Troubleshoot and debug user issues Provide operational and user-facing documentation We are looking for a Senior GenAI Platform Engineer with: Proven years of experience working with an object-oriented programming language (Python, Go, etc.) Experience with GenAI technologies like MCP, A2A, Langgraph, LlamaIndex, Pydantic AI, OpenAI APIs and SDKs A Degree in Computer Science, Engineering, Mathematics, similar field of study or equivalent work experience An understanding of Computer Science fundamentals such as data structures and algorithms An honest approach to problem-solving, and ability to collaborate with peers, stakeholders and management We give back to the technology community and you can read more about our outreach at: If indicated, please note that years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role.

Senior Software Engineer - Data Technologies, Non-Securitised Data - Macro & Industries Location London Business Area Engineering and CTO Ref # Description & Requirements Bloomberg is foremost a data company. Data is at the heart of everything we do; we collect it, cleanse it, enrich it, derive it, validate it, and make it available to our clients. This data is vast and varied and critical not only to our success but to that of our diverse global client base, and we continuously challenge ourselves to do this better and faster. We are a team of software engineers who build and maintain data pipelines for Bloomberg's Macro business areas, including Economics, Energy Transition, Physical Assets & Geo, Commodities & Carbon, and Macroeconomic Analysis. Working in close partnership with Bloomberg's Data department, we ensure that critical data and metadata flows reliably from source systems into Bloomberg's products, spanning ingestion, transformation, standardisation, enrichment, and downstream integration. Our engineers take ownership of their projects end-to-end, managing both technical delivery and stakeholder relationships. We also partner closely with infrastructure teams, contributing application-level insights that help guide platform improvements and influence infrastructure strategy. The breadth of domains we support gives you exposure to a broad and varied problem space. We care deeply about engineering craft. We build reusable components and shared libraries that solve cross-domain problems, abstracting away complexity so that common patterns are handled well in one place rather than duplicated across pipelines. We look for recurring challenges and invest in building tools that improve reliability, reduce risk, and make our teams more productive. This mindset means we are always looking for opportunities to raise the bar on performance, code quality, and maintainability. We are actively exploring how agentic and generative AI can augment our data workflows to improve data coverage and quality. We are also contributing to Bloomberg's semantic data initiatives, helping define how data flows into Bloomberg's enterprise knowledge graph. We value incremental delivery over big-bang releases. Getting our work into the hands of users early helps ensure we are building what the business needs. We foster a culture of psychological safety, collaboration, and continuous learning, where it's safe to ask questions, challenge ideas, and support each other to deliver under pressure. We'll trust you to: Take ownership of projects and drive them from design through to delivery Build robust, scalable data pipelines that process large volumes of complex data reliably Identify recurring problems across domains and build reusable solutions that benefit multiple teams Develop strong working relationships with engineering peers, data teams, and business stakeholders Champion engineering best practices, writing well-tested, maintainable, and high-quality code Deliver incrementally in a fast-paced environment, prioritising thoughtfully across competing workstreams You'll need to have: Strong backend experience with Python A degree in Computer Science, Engineering, Mathematics, a similar field of study, or equivalent work experience Experience building and maintaining data pipelines or ETL workflows Good system design and architecture skills Experience working with large distributed systems Experience of working with Kafka pipes Experience of working with high volume, high throughput, scalable data pipelines Experience working with big data pipelines and stores An understanding of continuous integration principles and writing testable code Experience using Linux/Unix We'd love to see: Experience integrating AI or machine learning into data pipelines or developer tooling A track record of leveraging AI to improve personal or team productivity Familiarity with event-driven architectures and message-based data processing Experience with data modelling or schema design Comfort working with diverse groups of stakeholders, both technical and non-technical A desire to get involved in department and company-wide initiatives If indicated, please note that years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role. Discover what makes Bloomberg unique - watch our podcast series for an inside look at our culture, values, and the people behind our success.

Bloomberg is seeking a Database Expert in London to enhance its Oracle infrastructure by automating database management and ensuring optimal performance. The successful candidate will work on building automation tools and troubleshooting complex issues within the Oracle databases. Key qualifications include deep Oracle experience, strong SQL and PL/SQL skills, and the ability to write automation software in Java or Python. Join Bloomberg and drive the development of scalable solutions for our engineering teams.

Bloomberg is the industry standard for financial data. Bloomberg's software solutions depend on robust data infrastructure to provide clients with this data. Our team is designing the next generation systems for managing this crucial infrastructure. Our ability to provide a DBaaS (Database as a Service) platform is critical to our clients' ability to retrieve and analyze massive quantities of data. Ensuring our services scale, are robust, secure, high-performing, and reliable is where you come in. The Oracle Infrastructure team, part of Bloomberg's Database Engineering organization, builds the self service infrastructure that enables engineers to effectively manage relational databases. Our mission is to be like a cloud provider that's optimized for Bloomberg Engineering's development needs. We are responsible for the infrastructure used to manage hundreds of Oracle database instances. To support this scale, we are recreating our database platform with a focus on security, performance, high availability, and self service. Our work sits at the intersection of infrastructure, developer experience, and data architecture, giving us unique visibility into Bloomberg's broader engineering landscape. We define database development best practices and leverage our collective experience to influence Bloomberg's database architecture design decisions. We are looking for a database expert with deep Oracle experience who also enjoys writing software and building automation. Someone who understands Oracle internals, performance tuning, and high availability architectures, and you believe in automating infrastructure and making things efficient where possible. We are ideally looking for someone who is comfortable in writing production quality code and debugging issues that span database, application, and infrastructure layers. Responsibilities Build Oracle focused automation to manage at scale database configuration, version management, and push button deployment. Automate the configuration and testing of Oracle high availability and disaster recovery solutions. Build backend tooling and services (Java/Python) that integrate with managed on premises Oracle environments. Improve monitoring, telemetry, and operational tooling. Troubleshoot complex Oracle performance issues using execution plans, wait events, and workload analysis. Promote database design and performance best practices across engineering teams. Collaborate with engineering teams and domain experts to design resilient and scalable solutions. Required Qualifications Strong hands on engineering experience building applications on top of Oracle databases. Deep knowledge of SQL and PL/SQL. Experience diagnosing and resolving Oracle performance issues. Experience writing software (Java or Python) to automate operational workflows. Ability to debug complex production incidents across database and application layers. Strong problem solving and communication skills. BA, BS, MS, or PhD in Computer Science, Engineering, or related technical field (or equivalent experience). Preferred Qualifications Experience administering Oracle at scale (Data Guard, ASM, RMAN). Experience building distributed systems or platform services. Familiarity with Kubernetes and containerized infrastructure. Experience with configuration management tools. Participation in database or open source communities. Years of experience are a guide; we will consider applications from all candidates who can demonstrate the required skills for the role.

Bloomberg is seeking a Senior Software Engineer in London to build and maintain data pipelines for various business areas. This position requires strong backend Python experience and the ability to work with complex data systems. The ideal candidate will manage projects end-to-end, collaborate with infrastructure teams, and champion engineering best practices. You will also explore AI integration into data workflows and help improve data quality.

Description & Requirements Bloomberg's Global Financial Networks - Distributed Ledger Product team is building the next generation of institutional market infrastructure across execution, clearing, and settlement workflows leveraging tokenized digital assets. As financial markets shift toward always on, programmable, and increasingly tokenized infrastructure, traditional workflows across markets remain highly fragmented-spanning execution, repo, collateral, clearing, settlement, custody across FIX feeds, files, APIs, used by asset managers, broker/dealers, market utilities, and vendor specific systems. Bloomberg is focused on modernizing these workflows by extending our Global Financial Networks into distributed ledgers and digital asset environments, building practical, regulated, institutional grade capabilities that help clients synchronize workflows, reduce reconciliation, support permissioned data sharing, enabling atomic transactions and asset mobility by connecting traditional financial infrastructures to emerging DLT networks. This work spans research and product development across permissioned networks, smart contracts, tokenized cash and stablecoins, tokenized assets and collateral, custody/wallet orchestration, and multi party workflows. We are seeking a DLT Product Manager to help define and build Bloomberg's DLT product strategy across execution, clearing and settlement workflows. You will work at the intersection of traditional capital markets and emerging digital asset infrastructure. The ideal candidate understands how institutional workflows operate today-especially in fixed income, OTC products, repo, collateral, settlement, and custody-and can translate that knowledge into product requirements for DLT enabled solutions. This role requires someone who can operate in ambiguity, explain complex concepts clearly, and build credibility with both technical and non technical audiences. You should be comfortable presenting to senior stakeholders, engaging with clients and partners, and helping Bloomberg determine where we lead, where we partner, and how we position our role in the evolving digital asset ecosystem. Responsibilities Convert complex market structure, technology, and workflow information into clear product direction for institutional digital asset capabilities. Help define Bloomberg's product strategy for DLT enabled trading and post trade workflows, smart contract workflows, wallet integration, node setup, permissioning, and multi party state synchronization. Evaluate how Bloomberg can extend existing Network assets into Distributed Ledger based workflows and technology. Partner with Engineering to translate DLT concepts into actionable requirements, technical designs, execution plans, and roadmap deliverables. Support node ledger choices, DevNet testing, operational runbooks, throughput and latency analysis, permissioning validation, and future evaluation of broader network roles. Partner with Legal, Risk, Compliance, and Security teams to evaluate regulatory, operational, custody, data sharing, licensing, and reputational considerations. Support internal education by creating clear presentations, product briefs, FAQs, and executive ready materials that explain DLT concepts in practical Bloomberg terms. Represent Bloomberg's DLT strategy in internal and external conversations with confidence, clarity, and commercial judgment. Prioritize use cases by balancing client demand, technical feasibility, regulatory readiness, commercial opportunity, and Bloomberg's right to win. Support go to market planning, product positioning, sales enablement, and client messaging for emerging distributed ledger capabilities. Maintain product documentation, workflow diagrams, implementation guides, partner notes, market research, and internal decision materials. Collaborate across teams with humility, urgency, and a strong sense of ownership. Qualifications 5+ years of Product Management/Development experience with proven experience within digital asset infrastructure. Experience in financial services required, such as experience in enterprise wide trading environments, critical financial operations or managing transactional flow with focus in technology. Understanding of interoperability ledger frameworks, token standards, identity models, or digital asset taxonomies. A collaborative mindset and comfort working with both technical and non technical teams. Strong written and verbal communication skills, especially when translating technical concepts into clear explanations. Excellent organizational skills and the ability to manage multiple workstreams. Curiosity and willingness to learn complex systems and industry standards. A strong interest in financial markets, DLT technologies and capabilities, and market workflows. Experience with project management, client support, and technical systems design is a plus. A proactive, problem solving attitude. Attention to detail is a must, especially when working on documentation, workflow diagrams, etc. If indicated, please note that years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role.