Hybrid AI Platform Engineer: Scale Regulated LLM Infra

Capgemini; Greater London; Hybrid; GBP 90,000 - 140,000; Full time

Benefits offered by this job

Applaud – peer recognition

Wellbeing program

Extensive training and certifications

Disability Confident Employer

Job summary

Capgemini is seeking a senior platform engineer to build the AI infra that powers our banks and insurers products. You will own end-to-end platform components, including model gateway, agent runtime, evaluation harness, and shared services, with a bias toward reliability, low latency, and cost efficiency.

You will work in a small, senior team, collaborating with product lines and engineering to ship self-service capabilities with clear documentation, sensible defaults, and governance for

Qualifications

• Strong production engineering: Python and a systems language, Kubernetes and IaC, plus one major cloud.
• Hands-on experience with LLM infrastructure and model gateway patterns.
• Experience with agent orchestration and eval gates in production.
• Post-training fluency in fine-tuning or data pipelines for models.
• Daily use of AI coding assistants in development workflows.

Responsibilities

• Own end-to-end platform components: model gateway, agent runtime, evaluation harness, guardrail engine.
• Build shared services and pipelines to support multiple product lines.
• Focus on reliability, latency, and cost optimization of platform services.
• Provide self-service surfaces with documentation and sane defaults.
• Collaborate with product teams to embed platform capabilities in new services.

Skills

Python

Go

Rust

Kubernetes

Infra-as-code

Cloud computing

LLM infra

Agent orchestration

Evaluation harness

Post-training

Tools

LangSmith

LangGraph

PostgreSQL

pgvector

ClickHouse

S3-compatible

Neo4j

Job description

Capgemini is seeking a senior platform engineer to build the AI infra that powers our banks and insurers products. You will own end-to-end platform components, including model gateway, agent runtime, evaluation harness, and shared services, with a bias toward reliability, low latency, and cost efficiency.

You will work in a small, senior team, collaborating with product lines and engineering to ship self-service capabilities with clear documentation, sensible defaults, and governance for