Senior AI Engineer
What’s In It For Me?
- A flexible holiday plan of up to 40 days per year
- £400 a year Wellbeing Allowance
- Private Medical Insurance
- Allowance for professional development books, E-books, and podcasts
- Contributory pension scheme
- Employee, friends and family discounts across 1200+ retail, hospitality and lifestyle brands
- Build and deliver production-ready AI and Generative AI solutions using LLMs, RAG architectures, and agents
- mplement and maintain retrieval pipelines using embeddings, vector databases, hybrid search, and effective chunking strategies
- Develop proof-of-concepts for emerging AI technologies and assess their production viability
- Write clean, maintainable code following established engineering best practices and quality standards
- Use AI coding assistants such as GitHub Copilot and Claude Code to accelerate development
- Participate in code reviews and architectural discussions to improve code quality and system design
- Work closely with Product and Engineering teams to understand requirements and deliver iterative solutions
- Collaborate with cross-functional partners (Security, Data, Operations) to ensure solutions meet quality, compliance, and scalability requirements
- Communicate technical decisions and tradeoffs clearly with both technical and non-technical stakeholders
- Contribute to improving AI development practices and tooling through feedback and suggestions
- Stay current with AI/ML developments, emerging frameworks, and best practices
- Learn from more experienced engineers and contribute knowledge back to the team
- Participate in capability-building activities and knowledge-sharing sessions
- Build expertise in production AI systems, model evaluation, and optimization techniques
- Solid software engineering experience with a focus on production Generative AI and RAG systems
- Demonstrated experience building and deploying AI systems in production environments
- Strong technical expertise in LLMs, RAG, prompt engineering, embeddings, and vector databases
- Hands-on experience with leading LLM providers (Anthropic Claude, OpenAI, etc.)
- Strong Python development skills and proficiency with AI coding assistants (Cursor, GitHub Copilot, Claude)
- Production experience with AWS cloud services and familiarity with containerization (Docker, Kubernetes)
- Solid understanding of ML fundamentals, model evaluation, and performance optimization
- Good communication skills with ability to collaborate effectively across teams
- Data engineering capability, including working with datasets, ETL pipelines, and metrics definition
Nice to have (but not essential)
- Experience with agentic workflow systems and complex orchestration patterns
- Background in NLP or contributions to open-source AI/ML projects
- Experience with model fine-tuning or custom training approaches
- Familiarity with MLOps platforms and experiment tracking tools
- Experience with infrastructure as code (Terraform, CloudFormation)
- Screening interview with the Talent Acquisition Partner
- First Stage Online Interview with the Director of AI Engineering
- Final Stage Online/In-Person Interview (3 stages: Technical, Product Team, VP Engineering)
We want every employee to feel comfortable bringing their passion, creativity, and individuality to work. We value all cultures, backgrounds, and experiences, because we believe diversity drives innovation and makes us stronger. Our approach to hiring and building teams is about more than filling roles - it’s about creating an environment where everyone can thrive, feel supported, and contribute to our mission of making the world a better place to work.