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 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
Click here to 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.
Technical Development & Execution
- 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
Collaboration & Problem-Solving
- 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
Learning & Growth
- 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
Essential skills
- 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
- 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)
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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)
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.
Reward Gateway is culture and client driven. We’re obsessed with putting the “Human” in HR and are proud to have been 100% dedicated to HR for over a decade. Since 2007, we’ve been right by the side of the world’s most innovative HR people, giving them beautiful products and tools they can use to attract, engage and retain their people.
The world’s most successful companies treat their people differently. They generate stock market returns of twice their peers and they have half the employee turnover. 76% of CEOs recognize that employee engagement is vital to their success but only 24% say they have a highly engaged company. Bridging that engagement gap is what drives us.
