Overview
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.
Responsibilities
* 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.
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