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About the role
Lead Gen AI Engineer/ Architect
London - Flexible Working Options Available
£80,000-£90,000 + Bonus + Benefits
Do you want to be at the heart of some of the biggest and most ambitious AI & Data programmes in the market?
We’re hiring experienced Lead GenAI System Architects to join a world-class AI Institute – a centre of excellence driving cutting-edge Engineering, AI & Data innovation.
You’ll work with senior leaders, global clients, and multidisciplinary teams on transformative Generative AI initiatives that redefine how organisations operate.
This is a senior, hands-on role for someone who blends deep technical expertise with the ability to influence at board and C-suite level.
- Shape and deliver enterprise-scale AI & Generative AI strategies aligned to real business outcomes.
- Design, build, and deploy end-to-end AI pipelines – from data ingestion to secure, scalable production systems.
- Lead the development and operationalisation of advanced models, including LLMs, diffusion models, and other generative techniques.
- Architect production-grade RAG systems, evaluation frameworks, and responsible AI guardrails.
- Stay at the forefront of AI research, translating emerging capabilities into practical, high-impact solutions.
- Mentor and lead cross-functional AI teams, building reusable assets and delivery excellence.
Background & Experience
- PhD or equivalent in Computer Science, ML, AI, or a related field (or outstanding equivalent experience).
- Extensive experience designing and deploying enterprise AI/ML solutions in production.
- Proven leadership of technical teams and senior stakeholders.
- Deep domain experience in regulated or data-rich industries (e.g. financial services, healthcare).
- Track record of thought leadership (publications, patents, open source, or industry impact).
Technical Excellence
- Expert Python and modern ML frameworks (PyTorch, TensorFlow).
- Strong experience with Generative AI tooling (e.g. LangChain, LangGraph or similar).
- Deep understanding of LLMs, prompt engineering, RAG, vector databases, evaluation, and security.
- Hands-on experience with fine-tuning, deploying, and monitoring large-scale GenAI systems.
- Strong MLOps / LLMOps capability: CI/CD, monitoring, governance.
- Cloud expertise across AWS, Azure, and/or GCP (cloud-agnostic preferred).
- Ability to communicate complex AI concepts to non-technical audiences.
