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-native AI platform services and public APIs that enable next-generation 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.