Senior Software Engineer — AI Platform & Cloud Services

Location: Cambridge, UK (hybrid) • Type: Full-time • Reports to: R&D Senior Manager

Join a fast-moving R&D team building cloud- AI platform services and public APIs that enable next- AI across multiple industrial products and partner ecosystems.

What you’ll do

Design, build and operate scalable, fault-tolerant cloud services on Microsoft Azure (AKS, Functions, API Management). Develop secure, production-grade public APIs and SDKs consumed by internal teams and external partners. Build platform capabilities around LLM deployment, RAG, agent orchestration, and model serving. Own security and privacy for AI workloads (authn/authorisation, data protection, auditability). Drive architecture, code reviews, and mentor more junior engineers. Ship prototypes quickly, then harden them for production — iterate with a builder’s mindset.

Must-have (clear and non-negotiable)

6+ years software engineering experience (platform / cloud service delivery). Strong hands-on experience with Microsoft Azure (AKS, Functions, API Management or equivalent). Proven track record building RESTful APIs and SDKs for external use. Practical experience with LLMs, RAG workflows, or agent patterns; able to explain tradeoffs (cost vs latency vs accuracy). Proficient in Python and familiar with PyTorch or TensorFlow. Solid understanding of security best practices for APIs (OAuth2, JWT, role scoping). Comfortable mentoring peers and leading technical designs.

Nice-to-have

Experience with .NET / C# in cloud services. Familiarity with orchestration frameworks (Semantic Kernel, AI Foundry, or similar). Experience with model evaluation/testing pipelines and automated QA for AI outputs. Knowledge of AI governance frameworks (NIST AI RMF, EU AI Act). Prior work on latency-sensitive or regulated industrial domains.

Why apply

High technical ownership: build the platform others rely on, influence roadmap and architecture. Blend of research & production: quick prototyping plus long-term, production quality engineering. Heavily collaborative, cross-disciplinary teams (data engineers, ML engineers, product). Competitive total rewards and professional development support. Flexible hybrid working.