Senior Machine Learning Engineer - Agentic AI Platform
other jobs Robert Half
Added before 4 Days
  • England,East of England,Cambridgeshire
  • Full Time, Permanent
  • Salary negotiable
Job Description:
Senior Machine Learning Engineer - Agentic AI Platform
Location: Central Cambridge (Hybrid) | Permanent | In partnership with Robert Half
The Opportunity
Join a global SaaS company building a cutting-edge multi-agent AI platform for enterprise data. This hands-on role focuses on scaling, hardening, and refining a graph-based agent engine as it moves toward global production.
What You’ll Do
*Agent Orchestration: Scale multi-step reasoning workflows and optimize agent collaboration.

*Tool Integration: Benchmark and extend toolchains within the agent framework.

*Inference & Performance: Optimize LLM integration, latency, and cost efficiency.

*State & Reliability: Strengthen Redis-backed persistence and ensure system consistency.

*Evaluation & Observability: Build regression frameworks and implement monitoring and tracing.

What We’re Looking For
*Strong Python engineering experience with production-grade systems

*Hands-on with LLM-powered applications and agent orchestration frameworks (e.g., LangGraph)

*Experience with stateful systems, caching, and reliability engineering

*Proficiency in FastAPI, Docker, and Redis

*Comfortable in a small, senior, high-impact team

Why Join?
*Work on a strategic next-gen AI platform

*Direct influence on architecture decisions

*Hybrid working in Central Cambridge

*Excellent benefits and discretionary bonus

Note: UK-based applicants only; full work rights required. No contractor/B2B/B2C roles available.
Robert Half Ltd acts as an employment business for temporary positions and an employment agency for permanent positions. Robert Half is committed to diversity, equity and inclusion. Suitable candidates with equivalent qualifications and more or less experience can apply. Rates of pay and salary ranges are dependent upon your experience, qualifications and training. If you wish to apply, please read our Privacy Notice describing how we may process, disclose and store your personal data:
Job number 3450021

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