Senior AI Engineer

Reward Gateway, part of Edenred, is a global leader in benefits and employee engagement. We help businesses attract, engage, and retain top talent through strategic reward, recognition, and well-being solutions.Guided by our shared missions - ‘Making the World a Better Place to Work’ and ‘Enriching Connections, For Good’ - we’re committed to transforming workplaces and improving people’s daily lives.Our team embodies entrepreneurial spirit, innovation, and respect. We push boundaries, speak up, and stay human, fostering a culture where imagination thrives.Your Role in Our Mission: As we continue to expand our business, we have an opportunity for a Senior AI Engineer to build and optimize production AI systems. You will work on the latest third-party AI services and frameworks, implementing LLMs, RAG architectures, and agentic workflows to boost internal tools, accelerate developer productivity, and elevate customer experience. You will collaborate with senior stakeholders across Product, Operations, and Engineering, translating business requirements into well-engineered technical solutions.What’s In It For Me?A chance to be part of an extremely well established, stable and high growth ‘Unicorn’ SaaS company with over 50 benefits in our employee benefits package, including:A flexible holiday plan of up to 40 days per year400 a year Wellbeing AllowancePrivate Medical InsuranceAllowance for professional development books, E-books, and podcastsContributory pension schemeEmployee, friends and family discounts across 1200+ retail, hospitality and lifestyle brandsClickhereto see our full suite of benefits and perks dedicated to supporting all aspects of employee wellbeing!Flexible, Hybrid Working:Collaboration, connection as a team, and strong internal relationships are part of the “RG Magic” that makes our culture thrive. Our teams work from our Dean Street office two days per week.What You’ll be Doing:Technical Development & ExecutionBuild and deliver production-ready AI and Generative AI solutions using LLMs, RAG architectures, and agentsmplement and maintain retrieval pipelines using embeddings, vector databases, hybrid search, and effective chunking strategiesDevelop proof-of-concepts for emerging AI technologies and assess their production viabilityWrite clean, maintainable code following established engineering best practices and quality standardsUse AI coding assistants such as GitHub Copilot and Claude Code to accelerate developmentParticipate in code reviews and architectural discussions to improve code quality and system designCollaboration & Problem-SolvingWork closely with Product and Engineering teams to understand requirements and deliver iterative solutionsCollaborate with cross-functional partners (Security, Data, Operations) to ensure solutions meet quality, compliance, and scalability requirementsCommunicate technical decisions and tradeoffs clearly with both technical and non-technical stakeholdersContribute to improving AI development practices and tooling through feedback and suggestionsLearning & GrowthStay current with AI/ML developments, emerging frameworks, and best practicesLearn from more experienced engineers and contribute knowledge back to the teamParticipate in capability-building activities and knowledge-sharing sessionsBuild expertise in production AI systems, model evaluation, and optimization techniquesExperience and Skills You Need in this Role:Essential skillsSolid software engineering experience with a focus on production Generative AI and RAG systemsDemonstrated experience building and deploying AI systems in production environmentsStrong technical expertise in LLMs, RAG, prompt engineering, embeddings, and vector databasesHands-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 optimizationGood communication skills with ability to collaborate effectively across teamsData engineering capability, including working with datasets, ETL pipelines, and metrics definitionNice to have (but not essential)Experience with agentic workflow systems and complex orchestration patternsBackground in NLP or contributions to open-source AI/ML projectsExperience with model fine-tuning or custom training approachesFamiliarity with MLOps platforms and experiment tracking toolsExperience with infrastructure as code (Terraform, CloudFormation)The Interview Process:Screening interview with the Talent Acquisition PartnerFirst Stage Online Interview with the Director of AI EngineeringFinal Stage Online/In-Person Interview (3 stages: Technical, Product Team, VP Engineering)At Reward Gateway | Edenred we are committed to ensuring an inclusive and accessible recruitment process for all candidates. If you have any specific requirements or need reasonable adjustments at any stage of the recruitment journey, please let your Talent Acquisition Partner know. Your needs are important to us, and we want to ensure an equitable experience for every candidate. Be comfortable. Be you. 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. DepartmentEngineeringEmployment TypeFull TimeWorkplace typeHybrid