This role develops generative AI applications using Java, Python, React or Angular, LangChain, LlamaIndex, Hugging Face, Docker, Kubernetes, and AWS, with tools like GitHub Copilot. You will build scalable, AI-powered solutions for Citi’s global finance operations.

At Axon Labs you will own production infrastructure across multi-region cloud and latency-sensitive environments using AWS, Python, C++, Kubernetes, Terraform, CI/CD, PostgreSQL, TimescaleDB, Kafka, Redis, low-latency messaging, Grafana, Prometheus, and Loki. The company is a systematic trading and research lab that builds decision engines running in live markets, with multiple strategies already in production across venues.

Citi★3.9 (21k)· London

Build and scale AI-powered financial systems using Java, Spring, React/Angular, Python, FastAPI, Docker, and GitHub Copilot within Citi’s global tech environment. You will design generative AI agents, LLM workflows, and RAG pipelines while working on enterprise microservices, mobile, or front-end development. This role is for an individual contributor on an agile team.

You'll develop Conveo's AI-powered consumer and B2B research platform using React, TypeScript, Node.js, PostgreSQL, and AWS/GCP infrastructure, with exposure to LLM APIs and prompt engineering. The role spans full-stack development—from API design to frontend implementation—plus direct customer interaction to translate research needs into technical solutions. You'll work autonomously on feature ownership within a small, high-performing engineering team at this Y Combinator-backed startup.

You will work with MongoDB, Postgres, Kinesis, Flink, Spark, ElasticSearch, Redis, Trino, Presto, Snowflake, Kubernetes, and public cloud. The Platform Engineering team designs and develops core data storage, streaming, caching, and indexing platforms that power Scale AI’s products for LLMs and generative models.

You'll work with Python (FastAPI), Go, TypeScript, PostgreSQL, Redis, Pinecone/pgvector, AWS (ECS, Lambda, SQS), Docker, Kubernetes, Terraform, LangChain/LlamaIndex, vLLM, and Anthropic/OpenAI APIs. You'll build and optimize RAG pipelines, real-time inference APIs, and vector search infrastructure powering LLM features for 500k+ monthly active users.

Work with Python/TypeScript, FastAPI/Flask/Express/NestJS, AWS/Azure/GCP, Kubernetes/Docker, Terraform, PostgreSQL/DynamoDB, and CI/CD tools. You will build core infrastructure for the Scale Generative AI Platform (SGP), designing scalable APIs, distributed data systems, and deployment pipelines for enterprise GenAI production

Ebury★3.3 (13)· London

Build an AI-powered financial crime investigation platform using React, TypeScript, FastAPI, Python, LangGraph, LlamaIndex, and AWS (Bedrock, ECS, DynamoDB, OpenSearch). Design AI agent workflows and micro-frontend architecture while mentoring engineers.

Elliptic★0.0· London

You'll design and build agentic workflows using LangChain or LangGraph, develop backend services in TypeScript and Node.js, and create evaluation frameworks for LLM outputs. Elliptic builds AI-powered compliance tools that help investigators trace blockchain fund flows and detect financial crime. You'll lead the AI team's technical direction, mentor junior engineers, and own significant features from design through production.

You'll work with TypeScript, Node, React, PostgreSQL, GraphQL, Temporal, MCP, and GCP to build Ravio's agentic compensation platform—moving from a traditional SaaS to a system of parent and specialist agents, durable workflows, and an eval harness. As a hands-on individual contributor, you will own architecture across the customer-facing web app, agentic platform, and shared infrastructure.

You’ll work with Python/TypeScript, FastAPI/Flask/Express/NestJS, AWS/Azure/GCP, Kubernetes, Docker, Terraform, PostgreSQL, and DynamoDB. You’ll build backend infrastructure for Scale’s Generative AI Platform, delivering APIs and distributed systems that bring GenAI into production for large enterprises.

You'll work primarily in Rust (or C++/Go) building xAI's API infrastructure that serves large language models to developers globally, handling billions of tokens per minute with low latency and high availability. Responsibilities span model serving, request routing, SDK development, rate limiting, observability, and scaling. You'll need expertise in distributed systems, databases like PostgreSQL and MongoDB, service reliability practices, and ideally experience with LLM inference engines like vLLM or TensorRT, plus Kubernetes and gRPC.