Why this job is important

AI is moving quickly but building AI that people can trust — and that works reliably at enterprise scale takes strong engineering discipline. In this role, you’ll help shape the future of our AI‑enabled enterprise platforms by bringing together AI engineering, software architecture, and data science to deliver systems that are scalable, secure, and responsibly designed. You’ll focus on turning real business needs into robust products: from designing how AI is embedded into platforms, to ensuring performance, monitoring, and governance are built in from day one.

What you’ll be doing

• Leading the design and delivery of AI‑enabled enterprise platforms, from early architecture through to production.
• Building and improving applied AI solutions (including LLM-based patterns such as embeddings, retrieval approaches, and model tuning where appropriate). [Principal_...ad_AI_0426 | Word]
• Setting engineering standards for MLOps: CI/CD, model deployment, monitoring, evaluation, and operational reliability.
• Architecting secure, cloud-native services (microservices, APIs, messaging/event-driven patterns) that support AI workloads at scale.
• Coaching engineers and collaborating across Engineering, Data Science, and Product to turn complex AI concepts into practical delivery plans.

The skills & experience needed

• Experience building, deploying, and maintaining machine learning and generative AI solutions (e.g., LLMs, embeddings, retrieval patterns, vector search, model fine‑tuning).
• Strong MLOps knowledge across continuous integration, deployment, monitoring, and evaluation of AI/ML models.
• Experience with AI infrastructure (orchestration pipelines, GPU compute, model hosting services) and scalable AI data structures (including vector databases/semantic search).
• Deep software engineering capability in .NET Core/C# and modern back-end engineering, with flexibility to work across languages such as Python, Go, or TypeScript.
• Strong understanding of distributed systems, microservices, cloud-native patterns, and modern data stores (SQL and NoSQL).
• Secure coding mindset with awareness of cybersecurity risks, particularly around AI and data privacy.
• Proven technical leadership (principal engineer/tech lead/architect level), with a track record of mentoring and influencing engineering direction.

What’s in it for you (UK benefits)

• Flexible hybrid working
• 25 days leave, 2 days paid for volunteering and life event leave
• Competitive salary and bonus (bonus dependent on role)
• Company pension
• Enhanced parental leave
• Healthcare options
• Wide range of flexible benefits

We are not able to offer visa sponsorship or assist with relocation support for this role. Please ensure you have the right to work in the country where this role is located before applying.