AI Engineer
AI Engineer (Generative & Agentic AI)
Permanent
Location: London (onsite twice a week)
Salary: £75,000 - £85,000 Per Annum D.O.E
Build intelligent systems that solve real enterprise problems:
We’re looking for an AI Engineer who wants to do more than just plug into APIs, someone who wants to own the build, shape intelligent systems, and bring advanced GenAI and Agentic AI solutions into real-world production.
If you’re motivated by tackling messy enterprise problems, not just experimenting with models, this is a role where you’ll build systems that genuinely change how organisations operate.
Why this role exists:
Enterprises are past the experimentation phase. They’re asking harder questions:
- How do we make GenAI stable, scalable, and safe?
- How do we move from prototypes to production?
- How do we integrate AI into existing products and workflows?
You’ll be the engineer who takes these questions and turns them into working, impactful AI systems, not just research pieces or demo-ware.
This role is ideal for someone who thrives on building, iterating, and owning AI solutions end-to-end.
The Role:
As an AI Engineer, you’ll be responsible for designing, building, and deploying production-grade AI systems in complex enterprise environments.
You will:
- Build and deploy GenAI, RAG, and Agentic AI systems that solve real business challenges
- Develop robust pipelines, services, and integrations that turn models into usable products
- Work across front-end, back-end, and data layers to deliver complete, functioning AI solutions
- Collaborate with architects, data scientists, and product stakeholders to shape solutions and define delivery paths
- Take ownership of performance, scalability, and maintainability of AI components
- Continuously experiment, improve, and bring new ideas forward, without heavy process slowing you down
This isn’t a research role and it’s not “keep the lights on.” It’s product-driven engineering where you ship real systems into production.
Key Responsibilities:
AI System Development
- Build and optimise AI models and pipelines
- Implement RAG, agentic workflows, and advanced reasoning techniques
- Deploy LLM-driven features into real products
Full-Stack & Platform Engineering
- Develop APIs, backend services, data flows, and integration layers
- Contribute to UI/UX when needed as part of end-to-end delivery
- Ensure clean, scalable engineering across the stack
MLOps / LLMOps
- Own the deployment, monitoring, and iteration of AI systems
- Use modern tooling to ensure models and pipelines are reliable, observable, and repeatable
Collaboration
- Work closely with cross-functional teams to identify opportunities and translate them into robust engineering solutions
- Provide technical input into architecture, design discussions, and delivery planning
What We’re Looking For:
Core Experience:
- Strong Python engineering skills and experience delivering production AI/ML systems
- Hands-on experience with LLMs, RAG, vector databases, and GenAI frameworks
- Experience deploying solutions on cloud platforms (AWS, Azure, or GCP)
- Familiarity with LangChain, LlamaIndex, or agentic frameworks is highly valuable
- Strong grounding in software engineering best practices (testing, versioning, CI/CD, scalability)
Mindset & Behaviours:
- Seek ownership, not just tasks
- Enjoy solving real user and business problems, not just model optimisation
- Thrive in environments where they can experiment and move quickly
- Communicate clearly with both technical and non-technical stakeholders
- Want to see their work in production, being used by real people
Why Join?
- Work on impactful AI programmes that go beyond prototypes
- Build meaningful, high-value systems that people actually use
- Work with modern GenAI tools, approaches, and delivery models
- Collaborate with experienced architects, engineers, and innovators
- Strong investment in engineering excellence, innovation, and personal development
If you want to build AI systems that matter, not just experiment with models, this is your next move.