12 jobs found

Who We Are Zoopla is a leading UK property website and trusted consumer brand, empowering movers to make better property decisions with over nine million monthly users generating over one billion annual property searches. Zoopla is more than a property portal. Over 5 million homeowners are subscribers, tracking their property values and providing a pipeline of movers for Zoopla's customers (estate agents and housebuilders). The business is investing in leveraging its scale and reach to build new, AI-driven experiences that engage movers and unlock value and a strong return on investment for customers. Our guiding behaviours define how we work together and what we expect from one another. These behaviours are to keep it simple, take ownership, make it better and win together. We strive for progress not perfection and have no doubt that we can achieve our ambitions if we focus on the right things, give it our all and do it together. What You'll Do As a Senior Analytics Engineer in the Data Analytics team, you'll own and develop the data modelling infrastructure, architecture and pipelines powering a wide range of data initiatives and data products. Own the analytics engineering workflow and architecture for the data modelling layer at the heart of the business. Ensure orchestration runs successfully, troubleshooting errors in key pipelines and empowering others to do the same. Effectively communicate and act as a liaison between highly technical and non-technical stakeholders, to translate business needs into engineering requirements. Deliver, and enable others to build, well defined, transformed, tested, documented, and code reviewed data sets. Due to the high quality of this data and the associated documentation, business users are able to self serve, analyse, and build products and services upon it, getting reliable, consistent results. Proactively seek automation and optimisation opportunities to constantly improve and develop the transformation layer, and unify its usage across multiple teams. Train, upskill and support others in dbt and data modelling best practices, applying software engineering practices to analytics code (version control, automated testing, continuous integration). We're looking for someone who: Has experience setting up & developing dbt architecture using CI/CD practices (essential) Is highly proficient with SQL and data modelling best practices for optimising performance (essential) Has previously worked with visualisation tools such as Tableau or PowerBI (essential) Is confident collaborating and communicating with non technical stakeholders (essential) Has experience integrating dbt with other tools in the modern data stack (essential) Is comfortable harnessing AI workflows to expedite development in a scalable, sustainable way (essential) Has experience working with Databricks and AWS (Glue, Lambda, Step Functions) or similar cloud platform (desirable) Where You'll Be At Zoopla we embrace hybrid working but emphasise the importance of also spending time together. You'll have the opportunity to work remotely (at home) for two days per week with Mondays and Thursdays as all Zoopla days in the office together plus a third in office day of your choosing. Our home in Tower Bridge is a wonderful hub for collaborative and individual working, with space to socialise and exercise. On our doorstep you'll find buzzing Borough, Bankside and Bermondsey, not to mention soaring river views. 25 days annual leave + extra days for years of service Day off for volunteering & Digital detox day Festive Closure - business closed for period between Christmas and New Year Cycle to work and electric car schemes Free Calm App membership Enhanced Parental leave Fertility Treatment Financial Support Group Income Protection and private medical insurance Gym on site in London 7.5% pension contribution by the company Discretionary annual bonus up to 10% of base salary

Who We Are Zoopla is a leading UK property website and trusted consumer brand, empowering movers to make better property decisions with over nine million monthly users generating over one billion annual property searches. Zoopla is more than a property portal. Over 5 million homeowners are subscribers, tracking their property values and providing a pipeline of movers for Zoopla's customers (estate agents and housebuilders). The business is investing in leveraging its scale and reach to build new, AI-driven experiences that engage movers and unlock value and a strong return on investment for customers. Our guiding behaviours define how we work together and what we expect from one another. These behaviours are to keep it simple, take ownership, make it better and win together. We strive for progress not perfection and have no doubt that we can achieve our ambitions if we focus on the right things, give it our all and do it together. What You'll Do As a Senior Analytics Engineer in the Data Analytics team, you'll own and develop the data modelling infrastructure, architecture and pipelines powering a wide range of data initiatives and data products. Own the analytics engineering workflow and architecture for the data modelling layer at the heart of the business. Ensure orchestration runs successfully, troubleshooting errors in key pipelines and empowering others to do the same. Effectively communicate and act as a liaison between highly technical and non-technical stakeholders, to translate business needs into engineering requirements. Deliver, and enable others to build, well defined, transformed, tested, documented, and code reviewed data sets. Due to the high quality of this data and the associated documentation, business users are able to self serve, analyse, and build products and services upon it, getting reliable, consistent results. Proactively seek automation and optimisation opportunities to constantly improve and develop the transformation layer, and unify its usage across multiple teams. Train, upskill and support others in dbt and data modelling best practices, applying software engineering practices to analytics code (version control, automated testing, continuous integration). We're looking for someone who: Has experience setting up & developing dbt architecture using CI/CD practices (essential) Is highly proficient with SQL and data modelling best practices for optimising performance (essential) Has previously worked with visualisation tools such as Tableau or PowerBI (essential) Is confident collaborating and communicating with non technical stakeholders (essential) Has experience integrating dbt with other tools in the modern data stack (essential) Is comfortable harnessing AI workflows to expedite development in a scalable, sustainable way (essential) Has experience working with Databricks and AWS (Glue, Lambda, Step Functions) or similar cloud platform (desirable) Where You'll Be At Zoopla we embrace hybrid working but emphasise the importance of also spending time together. You'll have the opportunity to work remotely (at home) for two days per week with Mondays and Thursdays as all Zoopla days in the office together plus a third in office day of your choosing. Our home in Tower Bridge is a wonderful hub for collaborative and individual working, with space to socialise and exercise. On our doorstep you'll find buzzing Borough, Bankside and Bermondsey, not to mention soaring river views. 25 days annual leave + extra days for years of service Day off for volunteering & Digital detox day Festive Closure - business closed for period between Christmas and New Year Cycle to work and electric car schemes Free Calm App membership Enhanced Parental leave Fertility Treatment Financial Support Group Income Protection and private medical insurance Gym on site in London 7.5% pension contribution by the company Discretionary annual bonus up to 10% of base salary

Software Engineer, Codex Enterprise Codex - Engineering - London, UK About the Team With Codex we're building an AI software engineer. One that you can pair with, delegate to, or even ask to take on future tasks proactively. Our team is a fast-moving group within OpenAI, bringing together research, engineering, design, and product. We iteratively build the Codex agent harness and product to get the most out of the model, and we iteratively train the model to be great at complex software engineering tasks. The Codex team is responsible for building state-of-the-art AI systems that can write code, reason about software, and act as intelligent agents for developers and non-developers alike. We operate across research, engineering, product, and infrastructure; owning the full lifecycle of experimentation, deployment, and iteration on novel coding capabilities. Codex Enterprise builds the ecosystem building blocks, discovery surfaces, and enterprise capabilities that help Codex spread across developers, teams, and organizations worldwide. It is a cross-cutting team that works across the stack to build both delightful product experiences and fundamental platform capabilities. Its customers range from individual developers and small teams to large enterprises, and our mission is critical to achieving the vision of Codex as a proactive teammate. About the Role As we grow, we're focused on turning Codex from a powerful individual tool into a production-grade teammate for entire organizations. You will work across internal OpenAI teams and external customers, from fast-moving startups to large enterprises, to make it possible to deploy, operate, and trust Codex in increasingly demanding real-world environments. As Codex's consumer adoption accelerates, enterprise demand is growing just as quickly, and there is also increasing opportunity to expand Codex through ecosystem capabilities that unlock new workflows, integrations, and discovery. This team helps turn messy, real-world team requirements into robust, repeatable, and scalable product and platform capabilities. You will work directly with a small set of deeply engaged design-partner customers using their real deployments to surface opportunities, and what's required for Codex to succeed inside modern engineering organizations. Those insights will drive what you build across product, infrastructure, deployment patterns, and ecosystem capabilities for all teams using Codex. This role owns systems end-to-end: from architecture and implementation to production operations with a strong bias for both quality and velocity. Responsibilities Shape the evolution of Codex by identifying how teams actually use (and break) AI-powered software engineering, and driving changes across product, infrastructure, ecosystem surfaces, and model behavior to make Codex a truly reliable teammate for organizations. Build the core ecosystem, team, and enterprise primitives that make Codex usable at scale, including plugins, skills, hooks, discovery surfaces, RBAC, admin and audit surfaces, usage, rate limits and pricing controls, managed configuration and constraints, and analytics that give teams and operators deep visibility into how Codex is being used. Design and own secure, observable, full-stack systems that power Codex across web, IDEs, CLI, and CI/CD, integrating with enterprise identity and governance systems (SSO/SAML/OIDC, SCIM, policy enforcement) and building data-access patterns that are performant, compliant, and trustworthy. Lead real-world deployments and launches by working directly with customers and the Go To Market team (GTM) to roll Codex out across teams, using live usage and operational signals to rapidly iterate and turn messy, real-world feedback into scalable product, platform, and ecosystem improvements. Qualifications Have strong software engineering fundamentals and experience turning ideas into productionized systems, thinking holistically about speed, performance, and user experience. Are proficient in one or more backend languages (e.g., Python, Go, Rust) and distributed systems concepts, with a focus on reliability, observability, and security. Enjoy building cross-cutting platform capabilities that unlock product velocity, and you're comfortable working across services, APIs, end-user product surfaces, and extensibility systems. Have experience with team/enterprise foundations such as identity and access (SAML/OIDC), SCIM, RBAC, audit/compliance logging, policy enforcement, and data governance controls. Like working directly with users/customers (or alongside GTM/solutions teams), and can translate messy, diverse requirements into opinionated implementations that scale across many teams. Enjoy 0 -> 1 environments, can navigate ambiguity, and bring crisp product thinking to technical trade-offs. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. Equal Opportunity Statement We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. Background Checks and Legal Compliance Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. Accommodations We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.

About the Team With Codex we're building an AI software engineer. One that you can pair with, delegate to, or even ask to take on future tasks proactively. Our team is a fast-moving group within OpenAI, bringing together research, engineering, design, and product. We iteratively build the Codex agent harness and product to get the most out of the model, and we iteratively train the model to be great at complex software engineering tasks. The Codex team is responsible for building state-of-the-art AI systems that can write code, reason about software, and act as intelligent agents for developers and non-developers alike. We operate across research, engineering, product, and infrastructure; owning the full lifecycle of experimentation, deployment, and iteration on novel coding capabilities. Codex Enterprise builds the ecosystem building blocks, discovery surfaces, and enterprise capabilities that help Codex spread across developers, teams, and organizations worldwide. It is a cross-cutting team that works across the stack to build both delightful product experiences and fundamental platform capabilities. Its customers range from individual developers and small teams to large enterprises, and our mission is critical to achieving the vision of Codex as a proactive teammate. About the Role As we grow, we're focused on turning Codex from a powerful individual tool into a production-grade teammate for entire organizations. You will work across internal OpenAI teams and external customers, from fast-moving startups to large enterprises, to make it possible to deploy, operate, and trust Codex in increasingly demanding real world environments. As Codex's consumer adoption accelerates, enterprise demand is growing just as quickly, and there is also increasing opportunity to expand Codex through ecosystem capabilities that unlock new workflows, integrations, and discovery. This team helps turn messy, real world team requirements into robust, repeatable, and scalable product and platform capabilities. You will work directly with a small set of deeply engaged design partner customers using their real deployments to surface opportunities, and what's required for Codex to succeed inside modern engineering organizations. Those insights will drive what you build across product, infrastructure, deployment patterns, and ecosystem capabilities for all teams using Codex. This role owns systems end to end: from architecture and implementation to production operations with a strong bias for both quality and velocity. In this role, you will: Shape the evolution of Codex by identifying how teams actually use (and break) AI powered software engineering, and driving changes across product, infrastructure, ecosystem surfaces, and model behavior to make Codex a truly reliable teammate for organizations. Build the core ecosystem, team, and enterprise primitives that make Codex usable at scale, including plugins, skills, hooks, discovery surfaces, RBAC, admin and audit surfaces, usage, rate limits and pricing controls, managed configuration and constraints, and analytics that give teams and operators deep visibility into how Codex is being used. Design and own secure, observable, full stack systems that power Codex across web, IDEs, CLI, and CI/CD, integrating with enterprise identity and governance systems (SSO/SAML/OIDC, SCIM, policy enforcement) and building data access patterns that are performant, compliant, and trustworthy. Lead real world deployments and launches by working directly with customers and the Go To Market team (GTM) to roll Codex out across teams, using live usage and operational signals to rapidly iterate and turn messy, real world feedback into scalable product, platform, and ecosystem improvements. You might thrive in this role if you: Have strong software engineering fundamentals and experience turning ideas into productionized systems, thinking holistically about speed, performance, and user experience. Are proficient in one or more backend languages (e.g., Python, Go, Rust) and distributed systems concepts, with a focus on reliability, observability, and security. Enjoy building cross cutting platform capabilities that unlock product velocity, and you're comfortable working across services, APIs, end user product surfaces, and extensibility systems. Have experience with team/enterprise foundations such as identity and access (SAML/OIDC), SCIM, RBAC, audit/compliance logging, policy enforcement, and data governance controls. Like working directly with users/customers (or alongside GTM/solutions teams), and can translate messy, diverse requirements into opinionated implementations that scale across many teams. Enjoy 0 1 environments, can navigate ambiguity, and bring crisp product thinking to technical trade offs. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link. OpenAI Global Applicant Privacy Policy

Role - Senior Enterprise Architect Technology - Enterprise Architect/Segment lead Location - UK/Europe Business Unit - STG Compensation - Competitive (including bonus) Job Description AI-First Solutioning, Human + Agent Ways of Working & Large-Scale Modernisation Your role This is a senior strategic role within the Enterprise Strategic Architecture practice, focused on defining and delivering next generation digital transformation programs for leading global organisations. The successful candidate will bring together deep technology expertise and strong business acumen to help clients navigate complex, large scale modernisation initiatives. As AI becomes central to how enterprises transform, this role is expanding in scope: the architect must be equally comfortable designing cloud native platforms, structuring human and agent collaborative workflows, and embedding AI driven capabilities as first class components of the overall solution. You will collaborate closely with sales and delivery teams across the full programme lifecycle - from shaping solutions during presales through to governing technical quality in delivery. You will engage with CDOs, CTOs, and senior digital leaders at client organisations, contribute to industry thinking through published viewpoints and speaking engagements, and play an active role in identifying emerging technology opportunities that can be developed into compelling propositions for the market. Responsibilities Strategic Thinking - Candidate can articulate where AI agents replace human tasks vs. augment them in a $10M+ transformation context. Can draw a human+agent operating model for a business process - showing handoff logic, oversight points, and accountability chains. Understands that LLM inference is now a line item in programme budgets and can estimate it at ROM level for a given use case volume. Design Depth - Has personally designed or reviewed an agentic system in production - e.g. a multi step reasoning pipeline, an autonomous code review agent, or a RAG powered enterprise knowledge layer. Can explain prompt architecture decisions (system prompt structuring, context compression strategies, few shot vs. zero shot trade offs) and how these affect both quality and cost. Understands model selection trade offs - when to use frontier models vs. fine tuned smaller models vs. cached completions. Token Optimization Fluency - Has operationalised token efficiency at scale - structured prompt libraries, semantic caching, chunk sizing for RAG pipelines, output length controls, batching strategies. Can model cost per transaction for an AI enabled workflow and present that as part of a business case. Understands how token spend interacts with context window limits across model families (GPT 4o, Claude, Gemini) and can make architecture trade offs accordingly. Must Have Skills Agentic architecture design - Multi agent orchestration, tool use design, human in the loop checkpoints, agent failure modes and recovery Human + agent workflow design - Task decomposition across human and AI agents; escalation paths; accountability mapping in regulated environments Expertise in leveraging coding agents - GitHub Copilot, Claude, Devin.ai and similar - to accelerate software delivery within a structured, governed engineering lifecycle Design and governance of automated delivery pipelines using tools such as Harness, GitHub Actions, ArgoCD and Tekton; trunk based development, progressive delivery and release automation Full stack application development - Architecture and delivery of modern full stack applications; proficiency across frontend frameworks, API layers, backend services, and data tiers at enterprise scale Modern CI/CD & delivery pipelines - Design and governance of automated delivery pipelines using tools such as Harness, GitHub Actions, ArgoCD and Tekton; trunk based development, progressive delivery and release automation High scalability integration - Architecting event driven and streaming integration at scale using Apache Kafka and Kafka Streams; asynchronous messaging patterns, schema registries, and real time data pipelines across distributed systems NoSQL & enterprise data platforms - Design of polyglot persistence architectures spanning NoSQL stores (MongoDB, Cassandra, DynamoDB), enterprise caching layers (Redis, Hazelcast, Memcached) and search platforms (Elasticsearch, OpenSearch) Hyperscaler resilience patterns - Building highly available, fault tolerant solutions on AWS, Azure and GCP - multi region active/active, chaos engineering, SRE practices, availability zone failover, and disaster recovery at cloud scale Token economics & LLM costing - Prompt compression, context window sizing, model tier selection, cost per transaction modelling at enterprise scale AI TCO & commercial modelling - Inference cost projections, build vs buy for foundation models, ROI framing for AI augmented delivery Digital transformation leadership - AI native programme design spanning cloud, integration, agentic capability layers and responsible AI governance Enterprise integration patterns - Streaming, API, event driven and real time patterns extending to RAG, vector stores, embedding services and LLM APIs as first class integration nodes Chief Architect leadership - Governing cross domain architect teams while managing AI risk, hallucination mitigation and responsible AI policy at programme level Multi cloud architecture (15+ yrs) - Hybrid IaaS/PaaS, multi az/region, IaC automation first, DevSecOps, K8s orchestration Influencing & stakeholder leadership - Builds and sustains networks across organisational boundaries through credibility and influence rather than authority; aligns diverse stakeholders - engineering, business, and executive - around a shared technology direction and drives teams to deliver outcomes in complex, matrixed environments CXO communication - Articulates at the right level of abstraction and detail from developer to board level Preferred Should be an excellent planner when it comes to release planning and other delivery planning. Should have excellent problem solving skills. Responsible for coaching and mentoring team members. BFSI/FS domain experience. Personal High analytical skills. High customer orientation. High quality awareness. Equal Opportunity Employer All aspects of employment at Infosys are based on merit, competence and performance. We are committed to embracing diversity and creating an inclusive environment for all employees. Infosys is proud to be an equal opportunity employer.

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 are looking for a Tech Lead - Data Engineering to serve as the primary architect and owner of our data platform. Reporting to the Head of Engineering, you will own the end-to-end technical direction of our data ecosystem and act as the most senior individual contributor in this domain. This role sits at the intersection of data engineering and system design. You will define how data is ingested, modelled, stored, transformed, and exposed across the company, with an emphasis on robust pipelines, clear data contracts, and reliable operation at scale. We are looking for someone who goes beyond building pipelines and focuses on designing durable, well-architected data systems. The large volumes of transactional data we generate form the foundation for machine learning and other AI-driven solutions that we are actively building and evolving. Your focus will be on designing and evolving data systems that are reliable, maintainable, and fit for long-term use, applying strong software engineering principles to how data is structured, integrated, and operated at scale. Responsibilities Own the Data Platform: Take end-to-end ownership of the data platform, including ingestion, storage, transformation, and exposure layers. This includes setting technical direction and being accountable for system reliability, performance, and cost. System Architecture: Lead the design of distributed data systems, ensuring clean integration between backend services, external APIs, event streams, and data storage layers. ML-powered Product Enablement: Work closely with product and engineering teams to design and lead data foundations for machine-learning-powered product features, ensuring data quality, traceability, and production readiness. Data Modelling & Strategy: Act as the lead architect for data models and contracts. Design schemas for both structured and unstructured data, balancing flexibility, performance, and long-term maintainability. Engineering Standards & Artefacts: Set and uphold engineering standards across the data domain. Produce and maintain architecture diagrams, design documents, and Architecture Decision Records (ADRs). Champion best practices including version control, CI/CD, modular design, backwards compatibility, and automated testing. Pipeline & ETL/ELT Design: Architect and implement high-scale, fault-tolerant data pipelines. Make deliberate trade-offs around latency, freshness, cost, and complexity, selecting fit-for-purpose tools rather than defaulting to trends. Hands-on Delivery: Spend a significant portion of your time building and maintaining core pipelines, schemas, and services in production. This is a hands-on role with direct responsibility for critical systems. Technical Leadership: Define the technical roadmap for data, perform deep code reviews, and mentor engineers on system design, SQL, and Python. Workflow Automation: Design and implement automated workflows (using tools such as n8n or custom Python services) to bridge operational gaps and reduce manual processes. Governance & Security: Design enterprise-grade governance frameworks covering access control, data lineage, observability, and data integrity. Production Ownership: Be accountable for production incidents, data quality issues, and cost regressions within the data platform. Experience and Qualifications Architectural Mindset: Proven experience as a Tech Lead, Principal Engineer, or System Architect designing and owning complex, distributed systems. Strong Software Engineering Foundations: A software-engineer-first mindset with deep experience in Python and production-grade engineering practices. Experience with libraries such as Pandas or Polars is expected, but architectural thinking matters more than specific tools. Machine Learning Exposure: Hands-on experience working with machine learning systems and tooling (e.g. Hugging Face, feature stores, model inference pipelines, or similar), with an emphasis on enabling ML in production rather than research experimentation. Database & Storage Expertise: Advanced SQL skills and hands-on experience with modern cloud data warehouses (e.g. Snowflake or equivalent), alongside solutions for unstructured or semi-structured data. ETL/ELT & Orchestration: Experience designing and operating modern data pipelines using tools such as dbt, Airflow, or equivalent orchestration and transformation frameworks. Engineering Rigor: Deep experience with Git-based workflows, CI/CD pipelines, automated testing, and maintaining long-lived systems in production. Engineering Judgement: Demonstrated ability to make and defend trade-offs-when to model data, when not to ingest data, and how to balance correctness, performance, and cost. Analytical Depth: Ability to interrogate and analyse data directly to validate system behaviour and ensure high levels of data quality. Desirable Experience with Analytics-as-Code platforms such as Looker/LookML. Experience building internal platforms that enable, rather than directly deliver, BI and reporting. Experience with automation platforms such as n8n for connecting operational systems. Experience designing systems for multimodal data (text, images, video, documents). Benefits As you can see, we are quickly progressing with our ambitious plans and are eager to grow our team of doers to achieve our vision of managing over 2 million properties through our platform across various countries. You can help us shape the future of property management across the globe. Here's what we offer: 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.

About StackOne: StackOne is the AI Integration Gateway for SaaS products and AI Agents. Backed by GV and Workday Ventures ($24M raised), we help builders of SaaS platforms and AI Agents orchestrate hundreds of scalable, accurate, and enterprise-grade integrations. Our platform combines 25,000 pre-mapped actions on 200 connectors, an AI-powered integration development toolkit, plus security by design: a real-time architecture, managed authentication and permissions, and end-to-end observability. Join us on our fast trajectory to build the future of agentic integrations. About the role We're looking for a Senior Platform Engineer to own how StackOne is built, shipped, and run, as we scale across our own cloud and into our customers' clouds. You'll own the infrastructure behind the platform, our deployment pipeline and developer tooling, and how we package StackOne to run inside customers' own AWS, GCP, or Azure accounts. It's a hands on role with broad scope. You write code and tooling, you own the IaC other engineers depend on, and you set the standard for how every new repository gets deployed and secured. You'll report directly to the CTO and work closely with our Security Engineer and tech leads. Responsibilities Own our infrastructure at scale: the AWS estate today (ECS Fargate, Aurora, ElastiCache, MSK, OpenSearch, Lambda, KMS) and the AWS CDK to Terraform migration. Keep it reliable, observable, and cost aware. Build out the deployment pipeline as we consolidate toward a monorepo: the CI/CD that ships every service, plus an automated end to end testing harness with incremental (affected only) testing that stays fast as we grow. Ship into customers' own clouds (self hosted / BYOC): the Terraform modules, container images, runbooks, and documentation for internal teams and customers. Own the release and upgrade path for self hosted customers: versioned, signed releases, a supported version policy, and a call home for usage and version reporting. Set the standard for new repositories: partner with the Security Engineer and tech leads so new projects (product, internal tools, and vibe coded prototypes) ship secure and deployable from day one. Templates and golden paths, not gate keeping. Raise reliability: SLOs, observability, and incident response. Make the system easy to operate when something breaks at 3am. Treat infrastructure as a product: paved roads and self serve tooling so product engineers ship without waiting on you. Use AI in the workflow: lean on LLMs and agents for IaC generation, test scaffolding, and runbook drafting, with guardrails you trust. What we're looking for 4+ years in platform, infrastructure, SRE, or DevOps, with hands on AWS at scale: ECS/Fargate, RDS/Aurora, Lambda, networking, IAM, KMS. Deep IaC ability: Terraform and/or AWS CDK, comfortable owning modules other teams build on. Strong CI/CD and monorepo build experience: caching and incremental/affected only test execution. You've made a slow pipeline fast. Strong coding in TypeScript, Python, or Go. You build tooling, not just YAML and configs. Containers in production (Docker); Kubernetes a plus. Security minded: you bake secure defaults into pipelines and repo templates, and partner with security rather than routing around it. A clear writer: docs and runbooks that internal engineers and external customers can follow. End to end ownership: you scope, ship, and measure, and automate instead of running manual checklists. Nice to have Shipping software into customers' own cloud or on prem (BYOC / self hosted), or a platform like Nuon, Replicated, or Omnistrate. Multi cloud (GCP or Azure) IaC, and exposure to Temporal, Kafka/MSK, ClickHouse, or OpenSearch. Our stack Cloud & infra: AWS (ECS Fargate, Aurora Postgres, ElastiCache, MSK, OpenSearch, Lambda, S3, KMS, CloudFront, WAF), Cloudflare (Workers, WAF) IaC: AWS CDK today, migrating to Terraform Data & messaging: Postgres, Redis, Kafka, OpenSearch, ClickHouse CI/CD: GitHub Actions Observability & analytics: Datadog, Sentry, Metabase Languages: TypeScript (Node.js), Python Benefits Meaningful share options (EMI) 25 days holiday + 1 additional day per year of tenure Private health insurance, including dental & optical £15/day London office lunch budget, up to £120/month £1,000 home office setup + £500/year top up Annual team offsite to sunny spots Join one of Europe's fastest growing startups Work with a veteran team of ex Google, Microsoft, Oracle, Coinbase, JP Morgan and more Health, fitness and gift card discounts; Cycle2Work and Electric Cars scheme London (hybrid, 2 days/week) preferred; open to remote within the UK We believe diversity drives innovation. We encourage individuals from all backgrounds to apply. As an equal opportunity employer, we celebrate diversity and are committed to creating an inclusive environment for all employees.