2 months ago
London, United KingdomSenior
Responsibilities
- Own one or more AI platform components end to end, including model gateways, agent runtimes, evaluation harnesses, guardrail engines, registries, or shared product services.
- Build pipelines that convert production traces and evaluation verdicts into reinforcement-learning and fine-tuning datasets.
- Train, evaluate, and serve internally tuned LLMs and SLMs alongside vendor models behind common quality gates.
- Own the reliability, latency, cost, and per-product-line cost attribution of platform services.
- Deliver documented, self-service platform surfaces with sensible defaults for product engineers.
- Embed with product teams to develop shared services and graduate proven capabilities into the platform.
- Create evaluation gates that detect regressions before client release and support production adaptation workflows.
Requirements
- Strong production engineering experience with Python, one systems language such as Go or Rust, Kubernetes, infrastructure-as-code, and a major cloud platform.
- Hands-on experience with LLM infrastructure, including model gateways such as LiteLLM or equivalent, model serving such as vLLM or managed endpoints, and vector or retrieval systems.
- Experience building agent systems with an orchestration framework such as LangGraph or first-party agent SDKs, including tool calling and MCP.
- Experience building or operating evaluation harnesses with golden datasets, CI regression gates, and LLM-judge calibration.
- Experience fine-tuning or post-training models, building the supporting data pipeline, or reproducing recent techniques in production systems.
- Daily hands-on use of AI coding assistants in software development.
- Preferred experience with guardrails or AI observability, reinforcement-learning infrastructure, SLM distillation, multi-tenant SaaS, financial or other regulated-industry engineering, security engineering, open-source contributions, or deployed agents and evaluation suites.
Benefits
- Hybrid work across company offices, client sites, and home, with no 100% work-from-home arrangement.
- Core and flexible benefits plus access to the Applaud peer-recognition portal.
- Wellbeing support through Mental Health Champions and apps including Thrive and Peppy.
- Training and development opportunities including thinktanks, hackathons, 250,000 courses, and external certifications.
- Disability Confident Employer Level 2 with an interview commitment for candidates who declare a disability and meet the essential criteria.
- Pre-employment checks include identity, nationality or immigration status, three years of employment history, and an unspent criminal-record check.
Tech Stack
Categories
About Capgemini
Capgemini is a global IT services and consulting firm that delivers strategy, cloud, AI, software engineering, and managed services to large enterprises and public-sector clients. Founded in 1967 and headquartered in Paris, it is publicly traded on Euronext Paris and operates in 50+ countries. The group expanded its engineering capabilities by acquiring Altran in 2020, now operating as Capgemini Engineering.