Hybrid AI Engineer

at Reward Gateway

• Job title: AI Engineer
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: £85,000 - £90,000 per year
• Degree requirement: Bachelor's Degree
• Tech skills: AWS, Cloud, Docker, ETL, JavaScript, Kubernetes, Node.js, PHP, Python, React, SQL, TypeScript
• Location requirements: Hybrid, London, United Kingdom

About the role

• AI Engineer developing scalable AI solutions at Reward Gateway | Edenred. Collaborating with teams to enhance internal tools and boost developer productivity.

Responsibilities

• Build and deliver production‑ready AI and Generative AI solutions using LLMs, RAG architectures, agents, and responsible AI practices.
• Use AI coding assistants such as Cursor, GitHub Copilot, and Claude Code.
• Manage cloud infrastructure and platform operations, including AWS, Kubernetes, CI/CD pipelines.
• Design, develop, and maintain backend services in Python, and contribute to React, TypeScript, and PHP codebases when required.
• Lead evaluation and iteration cycles, including defining and tracking offline and online metrics.
• Implement and maintain retrieval pipelines using embeddings, vector databases, hybrid search methods.
• Collaborate closely with Product using a working‑backwards approach.
• Improve internal AI development tooling.
• Mentor peers, conduct code reviews, and share knowledge to elevate engineering standards.

Requirements

• Proven experience in shipping production‑grade AI solutions.
• Applied AI expertise across LLMs, RAG, agentic workflows, prompt engineering, embeddings, vector databases, hybrid search techniques, and effective chunking strategies.
• Strong Python as a primary language, with solid testing practices and CI/CD experience; able to contribute when needed in React, TypeScript, and PHP or Node.js.
• Cloud and platform engineering skills, including AWS, Kubernetes, Docker, infrastructure as code, and modern observability tooling.
• Hands‑on experience with leading LLM providers such as Anthropic, Claude and OpenAI.
• Familiarity with LLM tooling ecosystems such as LangChain or LlamaIndex.
• Strong data engineering capabilities, including dataset creation and validation, ETL development, SQL schema design.
• Solid understanding of ML fundamentals and experimentation, including metric design, error analysis.
• A strong security and governance mindset, with the ability to communicate clearly

Benefits

• Online interview with the Talent Partner and the Director of AI Engineering
• Technical interview with Director of AI Engineering, VP of Product Engineering, and VP of Product
• Commitment to an inclusive and accessible recruitment process
• Environment where everyone can thrive, feel supported, and contribute to the mission