AI Platform engineer

Backend Engineer - AI Infrastructure & Data Platforms Location: London, UK (Hybrid - 2 days/week in office, Shoreditch) Salary: £65,000-£85,000 + equity Type: Full-time, Permanent

About the Role

We're scaling the backend systems powering our AI-driven product suite, including retrieval-augmented generation (RAG) pipelines, real-time inference APIs, and vector search infrastructure. You'll own the services that sit between our LLM providers and our customer-facing products, focusing on reliability, latency, and cost efficiency at scale.

What You'll Do

Design and maintain APIs serving LLM-powered features (chat, search, agentic workflows) to 500k+ monthly active users

Build and optimise RAG pipelines, including chunking strategies, embedding generation, and vector store management

Architect event-driven microservices using Kafka/SQS for async processing of high-volume inference requests

Implement observability and cost-tracking for token usage across multiple LLM providers (Anthropic, OpenAI, open-source models via vLLM)

Own database performance for both relational (Postgres) and vector (pgvector/Pinecone) workloads

Collaborate with ML engineers on model-serving infrastructure and prompt-caching strategies

Drive API versioning and backwards compatibility as the product iterates quickly

Core Tech Stack

Languages: Python (FastAPI), Go, TypeScript (Node.js)

Databases: PostgreSQL, Redis, Pinecone/pgvector

Infra: AWS (ECS, Lambda, SQS/SNS), Docker, Kubernetes, Terraform

AI/ML tooling: LangChain/LlamaIndex, vLLM, Anthropic & OpenAI APIs, embedding models

Observability: Datadog, Grafana, OpenTelemetry

CI/CD: GitHub Actions, ArgoCD

Requirements

4+ years backend development experience, ideally with at least 1 year working with LLM/AI-integrated systems

Strong grasp of asynchronous architecture and distributed systems fundamentals

Experience with vector databases or semantic search implementations

Comfortable working directly with LLM APIs (rate limits, streaming responses, token cost optimisation)

Solid understanding of API design, security, and scalability best practices

Nice to Have

Experience fine-tuning or evaluating open-source models

Familiarity with agentic frameworks (function calling, tool use, MCP)

Prior startup/scale-up experience

Benefits

25 days holiday + bank holidays

Private healthcare (Vitality)

£1,000 annual learning budget

Hybrid working with full WFH equipment provided