Job Description
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