AI Product Engineer: Build End-to-End Auditor Platforms

Dex; Greater London; Sur place; GBP 70 000 - 110 000; Plein temps

Résumé du poste

Dex is partnering with a startup building the first AI-native certification body to independently assess AI systems for security and reliability. The Product Engineer will own end-to-end development across the front end, back end, and AI-agent infrastructure.

You will design and implement full-stack features, build the core agent infrastructure, and define safeguards like sandboxing and containment. Join a founding team shaping how AI systems are audited.

Qualifications

• Shipped real systems with substantive decisions on agent harnesses, evals, sandboxing, or multi-component system/tool design.
• Proven ability to ship across the interface, backend, data, and deployment layers.
• Evidence of exceptional output: open-source contributions, personal projects, research, or hackathon results.

Responsabilités

• Design and implement full-stack product features, from user interface to backend services.
• Build the core AI agent infrastructure and evaluation frameworks for system certification.
• Define and implement critical safeguards for AI systems, including agent sandboxing and hallucination containment.
• Drive product development from initial concept through to production deployment, ensuring direct impact on audit outcomes.
• Contribute to the technical architecture and foundational engineering practices of a nascent team.

Connaissances

Shipped real systems

Full-stack delivery

First-principles thinking

Evidence of output

Description du poste

Dex is partnering with a startup building the first AI-native certification body to independently assess AI systems for security and reliability. The Product Engineer will own end-to-end development across the front end, back end, and AI-agent infrastructure.

You will design and implement full-stack features, build the core agent infrastructure, and define safeguards like sandboxing and containment. Join a founding team shaping how AI systems are audited.