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.
1. Shape and deliver enterprise-scale AI & Generative AI strategies aligned to real business outcomes.
2. Design, build, and deploy end-to-end AI pipelines – from data ingestion to secure, scalable production systems.
3. Lead the development and operationalisation of advanced models, including LLMs, diffusion models, and other generative techniques.
4. Architect production-grade RAG systems, evaluation frameworks, and responsible AI guardrails.
5. Stay at the forefront of AI research, translating emerging capabilities into practical, high-impact solutions.
6. Mentor and lead cross-functional AI teams, building reusable assets and delivery excellence.
Background & Experience
7. PhD or equivalent in Computer Science, ML, AI, or a related field (or outstanding equivalent experience).
8. Extensive experience designing and deploying enterprise AI/ML solutions in production.
9. Proven leadership of technical teams and senior stakeholders.
10. Deep domain experience in regulated or data-rich industries (e.g. financial services, healthcare).
11. Track record of thought leadership (publications, patents, open source, or industry impact).
Technical Excellence
12. Expert Python and modern ML frameworks (PyTorch, TensorFlow).
13. Strong experience with Generative AI tooling (e.g. LangChain, LangGraph or similar).
14. Deep understanding of LLMs, prompt engineering, RAG, vector databases, evaluation, and security.
15. Hands-on experience with fine-tuning, deploying, and monitoring large-scale GenAI systems.
16. Strong MLOps / LLMOps capability: CI/CD, monitoring, governance.
17. Cloud expertise across AWS, Azure, and/or GCP (cloud-agnostic preferred).
18. Ability to communicate complex AI concepts to non-technical audiences.