4 days ago
Base Salary
$129k - $143k/yr
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 training and adaptation pipelines that convert production traces and evaluation verdicts into reinforcement learning and fine-tuning datasets.
- Develop infrastructure to train, evaluate, and serve tuned large and small language models behind common platform gates.
- Own the reliability, latency, and cost baselines of platform services.
- Provide documented, self-service platform components with sensible defaults for product engineers.
- Embed with product teams to develop shared services and graduate proven components into platform services.
- Build and operate agent orchestration, tool-calling, Model Context Protocol, evaluation, observability, guardrail, and multi-tenant infrastructure.
Requirements
- Strong production engineering experience with Python, one systems language such as Go or Rust, Kubernetes, infrastructure-as-code, and a major cloud provider.
- Hands-on experience with LLM infrastructure, including model gateways, model serving, and vector or retrieval systems.
- Experience building with agent orchestration frameworks and understanding tool calling and the Model Context Protocol.
- Experience building or operating evaluation harnesses with golden datasets, CI regression gates, and LLM-judge calibration.
- Post-training experience through model fine-tuning, post-training, production data pipelines, or reproducing recent research techniques in production.
- Daily hands-on use of AI coding assistants in software development.
- Depth in four or five relevant areas is valued more than surface familiarity across all areas.
- Preferred experience includes guardrail engines, AI observability, reinforcement learning infrastructure, SLM distillation, multi-tenant SaaS, financial or regulated-industry engineering, security engineering, open-source contributions, or deployed agents and evaluation suites.
Benefits
- Base compensation range is 129,000 to 143,000, with possible additional variable compensation, bonuses, or commissions.
- Comprehensive benefits for eligible regular full-time employees, including paid time off, holidays, personal days, sick leave, medical, dental, vision or provincial healthcare coordination, retirement plans, life and disability insurance, and employee assistance programs.
- The role is designed around self-service platform engineering, human review gates, and collaboration with product teams; no separate QA function or scrum masters are specified.
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.