Lead AI Engineer - Permanent - London/Hybrid
* Permanent
* Hybrid in Central London
* Competitive Salary
Key Responsibilities
Strategic & Architectural Leadership
* Define and own the technical vision and architecture for AI solutions across the organization
* Evaluate, select, and standardize AI technologies, frameworks, and third-party services
* Lead technical design reviews and make critical architectural decisions for complex AI initiatives
* Drive technical strategy for responsible AI, model governance, and production ML operations
* Partner with senior leadership (CTO, VPs, Directors) to translate business objectives into technical AI roadmaps
* Influence product and engineering strategy through technical insights and feasibility assessments
Technical Expertise & Execution
* Act as the go-to technical expert for complex AI challenges across engineering teams
* Lead proof-of-concepts for emerging AI technologies and assess their production viability
* Build and deliver production-ready AI and Generative AI solutions using LLMs, RAG architectures, agents, and responsible AI practices
* Implement and maintain retrieval pipelines using embeddings, vector databases, hybrid search methods, and effective chunking strategies
* Use AI coding assistants such as Cursor, GitHub Copilot, and Claude Code to accelerate development while maintaining ownership of outcomes and documenting best practices
Standards & Enablement
* Establish and enforce engineering best practices, coding standards, and quality benchmarks for AI development
* Improve internal AI development tooling, including shared libraries, SDKs, and reference implementations for RAG, tracing, prompt management, and evaluation
* Mentor engineers across all levels, conduct code reviews, and elevate engineering standards across the organization (upgraded from \"mentor peers\")
* Lead internal enablement and capability-building activities across the organization (upgraded from \"contribute to\")
Cross-functional Collaboration
* Collaborate closely with Product using a working-backwards approach, producing technical designs, breaking down work, and delivering iteratively
* Partner with Security, Legal, and Data teams to define AI policies, review risks, and ensure privacy, PII protection, and regulatory compliance
Skills, Knowledge and Expertise
Must Have:
* 7+ years of software engineering experience with 3+ years focused on production Generative AI and RAG systems
* Demonstrated experience architecting and scaling complex AI systems in production environments
* Proven track record of technical decision-making and architectural leadership with measurable business impact
* Deep technical expertise in LLMs, RAG, agentic workflows, prompt engineering, embeddings, vector databases, and hybrid search techniques
* Hands-on experience with leading LLM providers (Anthropic Claude, OpenAI), including model selection, evaluation, and optimization
* Expert-level Python development skills and fluency with AI coding assistants (Cursor, GitHub Copilot, Claude)
* Production experience with AWS cloud services and container orchestration (Kubernetes), including infrastructure design for ML workloads
* Strong technical communication skills with ability to influence senior stakeholders and drive consensus across teams
* Strong data engineering capabilities, including dataset creation, ETL development, and metrics definition (moved from Nice to Have)
* Solid understanding of ML fundamentals, experimentation methodologies, and model performance optimization (moved from Nice to Have)
Nice to Have
* Experience with model fine-tuning, RLHF, or custom training approaches
* Familiarity with MLOps platforms and experiment tracking tools
* Experience with infrastructure as code (Terraform, CloudFormation)
* Background in NLP research or open-source AI/ML contributions