AI Product Engineer

AI Product Engineer - AI/Hardware/Manufacturing

Location: Central London, primarily office-based with some flexibility.

We're partnering with an AI startup building software to help engineers design and develop physical products faster. Combining machine learning with complex engineering software, their platform helps bring newhardware ideas closer to production.

They're looking for anAI Product Engineer to build the interface between users and their AI-powered design systems. This is a hands-on opportunity to work across frontend, backend, and applied AI, helping engineers turn ideas into structured workflows and inspect and refine the results.

What you'll be doing

• Build polished applications that help engineers describe, generate, and refine designs.
• Translate natural-language requests, images, and drawings into structured engineering specifications.
• Designagentic systems that interact reliably with tools, backend services, and CAD and geometry systems.
• Evaluate models, investigate failures, and decide when adaptation or fine-tuning is needed.
• Create workflows that let users review, correct, and guide AI-generated outputs.
• Own features across frontend, backend, and applied AI, from initial design through implementation.

What we're looking for

• Strong product-engineering fundamentals and experience delivering user-facing software.
• A deep understanding ofLLM behaviour , beyond prompting and basic API integration.
• Experience building agents that use tools and interact with backend services.
• Sound judgement around model selection, evaluation, and reliability.
• Confidence translating ambiguous user needs into practical product features.
• The ability to work across frontend, backend, and applied ML within a small, highly technical team.

Experience that would stand out

• React, TypeScript, Python , and modern application architecture.
• Structured generation, tool use,RAG , model adaptation, or fine-tuning.
• Multimodal systems involving text, images, drawings, or technical inputs.
• Evaluation frameworks, observability, and testing for AI systems.
• CAD, geometry, engineering software, or human-in-the-loop workflows.

We're interested in engineers who combine strong coding skills, a practical understanding of AI, and thoughtful product decisions to build software that works reliably for users.