Work with Java, GitHub Copilot, Devin.AI, Citi Squad, Stylus Workspaces (Gemini, OpenAI, Claude, Llama), Docker, Kubernetes, and CI/CD. Build high-performance, real-time FX risk management systems for a greenfield platform with a 10+ year strategic commitment. As a VP, lead end-to-end delivery and technical direction.

Build with Python, Go, or Java on the backend, and React/TypeScript on the frontend, using PostgreSQL and non-relational stores, with Docker, Kubernetes, and cloud infrastructure (AWS, GCP, Azure). This role owns full-stack delivery of the B2B product—a campaign, device management, and insights platform for retail and brand partners—along with API design and distributed systems. The team includes engineers, product, and platform groups, working closely with the Head of B2B Product.

You'll work with PyTorch, distributed training, Docker/K8s/IaC, and Python backend. The company builds foundation models for extreme physics to accelerate progress in semiconductors, aerospace, defence, and fusion. Joining a small, research-heavy team, you'll be the first dedicated engineering owner for the ML stack.

You'll work with Python (FastAPI), Postgres, Redis, Docker/Kubernetes, and AWS. As a founding London engineer, you'll own production services and build scalable backend systems for a commodity e-commerce and electronic trading platform provider.

Build and launch AI-powered products using TypeScript, React, Node.js, Rust, Azure, Docker, and LLM APIs (OpenAI, Anthropic). As the founding product engineer, you’ll own the full stack—from frontend and backend to AI workflows—and work directly with founders to shape product direction from 0 to 1.

Build scalable backend services, APIs, and cloud-native systems on AWS running Kubernetes, using TypeScript, Node.js, Docker, and React. You will work directly alongside AI Engineers to build the production platform behind their next-generation AI authentication product.

You'll work with Python (Flask/Django), React/NextJS, Docker, and LLMs to build agentic AI workflows. The platform automates risk engineering for commercial insurance, transforming manual workflows from days into minutes. As founding engineer (#7), you'll shape the technical foundation with ex-QuantumBlack founders.

You will build and deploy production trading infrastructure using Python, FastAPI, Postgres, Redis, Docker/Kubernetes, and AWS. As a founding member of the London engineering team, you'll design and own high-performance APIs and backend services for the company’s electronic commodity trading platforms. No team size or scope is stated.

You will work with Python, TypeScript, AWS, PostgreSQL, Docker, and CI/CD to build real-time systems, scalable backend services, agentic AI, and operational tooling. The team is building the real-time control layer for complex physical operations, starting with a live platform at a major international airport that coordinates people, equipment, and workflows.

Head of Quality Engineering to own quality across the organisation, working with PHP, Kotlin, GO, Python, Typescript, React, React Native, GraphQL, Relay, PHPUnit, Behat, JUnit, Kotest, Jest, Maestro, K6, Datadog, Sentry, Incident.io, Grafana, AWS, Docker, Kubernetes, RabbitMQ, Argo, Github, and Github Actions. The role will lead the use of AI (LLMs) for testing and will manage a team of approximately two Quality Engineers while being hands-on with code and CI pipelines. Lendable builds technology for consumer credit and savings products.

Build the platform using Python, TypeScript, Go, Java, REST APIs, AWS, PostgreSQL, Docker, and CI/CD. This early-stage venture creates the payments layer for connected vehicles, automating detection and settlement of road charges for rental and fleet operations.

You'll work with Python (FastAPI), JavaScript/TypeScript (React), Docker, Postgres, Kafka, and Redis. Your project builds a dataset to evaluate AI coding agents by creating realistic simulated developer environments, designing challenging tasks, and writing verification tests.

You will work with Ruby on Rails, PostgreSQL, Redis, Sidekiq, Vue.js, AWS, Docker, GitLab, and Cloudflare. You will take ownership of core product development, platform improvements and technical decision-making for a SaaS platform in the health, fitness and coaching technology sector.

You'll lead Python and FastAPI development on Lendable's Data Team, building data pipelines, APIs, and services deployed via Docker, Kubernetes, and AWS with ArgoCD. The fintech company rebuilds consumer finance products (loans, credit cards, car finance) to serve UK and US markets faster than traditional banks. You'll mentor a small team of 1–2 engineers while owning technical direction and remaining hands-on with code.

This role works with Python, SQL, REST APIs, OAuth, event-driven architecture, Airflow/Prefect/Dagster, AWS/GCP/Azure, Docker, Kubernetes, Microsoft 365, and Microsoft Copilot. As the deep technical engine behind a Global FinTech’s internal AI deployment team, you own infrastructure from data pipelines to system integrations, taking prototypes to production.

You will architect a cloud-native backend on GCP using Python, C++, Docker, and Cloud Run, with emphasis on data-intensive or realtime systems. The deep-tech startup scales a research-led product into a production platform, collaborating with robotics/computer vision engineers to build APIs for edge devices.

You will work with TypeScript/JavaScript, React, Playwright or Cypress, Azure, and CI pipelines (Azure DevOps/GitHub Actions) to own quality for a modern React website augmented with an AI assistant, serving data exploration, charts, and dashboards. You will define test strategy, build automation frameworks, and test AI behaviour including guardrails.

You will work with React, Next.js, Node.js, Python (FastAPI), Docker, and cloud platforms like Cloud Run. You will build and accelerate Sherwood, a platform that houses project data, monitoring, and verification outputs for nature-based carbon projects and ecological restoration. This is a senior individual-contributor role on a small, high-impact team.

You will work with AWS, Kubernetes (EKS), Terraform, Docker, Helm, CircleCI, Datadog, Cloudflare, Go, GraphQL, gRPC, MySQL, PostgreSQL, Redis, and GCP. The role owns infrastructure, developer experience, and platform reliability for a fast-growing workspace technology company. This is a hands-on engineering position spanning Platform Engineering, DevOps, Cloud Security, and backend development.

Work with React, TypeScript, Node, REST APIs, SQL, and relational databases. You’ll join a climate-tech startup’s 15-person development team building a platform that helps homeowners transition away from fossil fuel heating.

React, TypeScript, Node, Postgres, Tailwind, Docker, SQL, REST APIs. Build a platform driving the transition from fossil fuel heating in homes, reducing carbon emissions and energy bills. Join a 15-person development team.

You will design and build the agent sandboxing platform using Go or Rust, working with containerization (Docker, Firecracker, gVisor) and virtualization technologies on Linux. The team provides a secure, high-performance code execution layer for agentic workflows deployed across internal and customer-managed environments.

Design AI solutions using Aion's enterprise platform, Large Language Models, Generative AI, RAG, AI agents, and cloud services (AWS, Azure, GCP) with Kubernetes, Docker, APIs, and microservices. You will partner with enterprise customers to architect and deliver production-ready AI applications, guiding them from concept to deployment on a unified platform.

Lead a hands-on engineering team building a greenfield Agentic AI Platform for banking workflows using Python, Java/Spring Boot, and Go, with LLM/agentic frameworks (Google ADK, LangChain), GCP, Vertex AI, Elastic, Pinecone, Databricks, Kafka, Kubernetes, and Terraform. You will drive architecture, code, and mentor a new team of software and ML engineers.

Citi★3.9 (21k)· London

Lead architecture and hands-on development of a greenfield Agentic AI Platform on GCP using Vertex AI, ADK, LangChain, multi-agent architectures, and RAG with Python, Java/Spring Boot, and Kubernetes. The platform empowers Citi’s corporate and investment bankers with autonomous agents to streamline workflows and deepen client relationships.