Overview We're looking for a skilled Generative AI Engineer to help build and scale a modern AI platform within a large, complex enterprise environment. This role combines hands-on Python development with DevOps practices and the integration of large language models into secure, production-grade systems.

You'll be working on emerging technologies, solving real-world engineering challenges, and contributing to the evolution of AI capabilities in a regulated setting.

Key Responsibilities

• Design, build, and maintain backend services and APIs that provide secure access to AI capabilities
• Develop Python-based components for prompt orchestration, output validation, and evaluation workflows
• Integrate LLMs into existing enterprise systems, ensuring alignment with security and observability standards
• Implement and manage CI/CD pipelines in line with engineering best practices
• Collaborate with cross-functional teams (engineering, platform, and operations) to ensure reliable deployment and scaling
• Support experimentation, benchmarking, and cost/performance analysis of AI models
• Contribute to retrieval-augmented generation (RAG) solutions and data integration patterns
• Establish reusable API standards, frameworks, and documentation to support wider adoption
• Troubleshoot and optimise distributed systems and cloud-based services

Core Skills & Experience

• Strong background in backend engineering using Python (additional exposure to Node.js or similar is beneficial)
• Hands-on experience working with Generative AI and large language models
• Understanding of prompt engineering challenges and model evaluation techniques
• Solid DevOps capabilities, including CI/CD pipelines and monitoring practices
• Experience operating in secure, regulated environments with strict governance controls
• Proven track record of integrating AI into production applications or workflows
• Knowledge of authentication, secrets management, and secure system design

Nice to Have

• Experience with API gateways, service meshes, or GitOps tooling
• Familiarity with cloud platforms and services (compute, containers, storage, messaging)
• Experience building RESTful APIs (FastAPI or similar) and microservices architectures
• Exposure to infrastructure-as-code and automated deployment workflows
• Knowledge of prompt evaluation tooling
• Experience with both SQL and NoSQL databases
• Understanding of vector search and retrieval-based AI patterns

Ways of Working

• Takes initiative and solves problems without needing heavy direction
• Comfortable navigating ambiguity in a fast-evolving technical landscape
• Strong communicator who can work effectively across technical and non-technical teams
• Curious and proactive in exploring new AI approaches responsibly
• Focused on automation and efficiency to improve delivery

What Good Looks Like

• High-quality, secure AI services delivered into production
• Improved team productivity through automation and streamlined processes
• Reliable, observable systems with performance and evaluation built in
• Solutions that are easy for other teams to adopt and build upon
• Clear, accessible documentation supporting rapid onboarding