Director - Product Technology

We are looking for a Director - Product Technology, Platforms to lead the technical evolution and productization of Inception42’s shared agentic-AI platform. You will help turn advanced AI capabilities into secure, reliable, and scalable experiences for enterprise and government customers — connecting product ambition with engineering execution and helping teams move from early validation to dependable deployment at scale.

Reporting to the Senior Director of Product Technology, you will set technical direction, shape architecture, bring together the right engineering and AI capabilities, and guide the platform from concept through production. You will partner closely with Product, Design, Engineering, Data & AI, Platform, Security, Delivery, and strategic technology partners, including Microsoft. Success requires strong technical and product judgment across usability, reliability, speed, security, deployment constraints, and AI economics.

Senior product-engineering leadership experience building complex enterprise platforms, developer products, or multi-tenant SaaS.

Strong hands-on technical credibility in architecture, system design, design or code review, and complex production diagnosis.

Deep understanding of distributed systems, APIs, identity, security, multi-tenancy, reliability, observability, and production operations.

Experience shipping AI-powered products, with practical knowledge of agents, RAG, evaluation, grounding, safety, latency, and cost.

Experience guiding products from early discovery and prototypes through launch, production operation, iteration, and scale.

Strong product judgment grounded in user and developer workflows, usability, adoption, and measurable value.

A track record of leading across organizational boundaries and bringing clarity to complex technical and commercial trade-offs.

Ability to bring structure and clarity to ambiguous environments while keeping teams moving without unnecessary process.

Clear communication with engineers, researchers, executives, customers, and strategic partners.

Experience with agent platforms, copilots, workflow systems, developer platforms, or API ecosystems.

Exposure to sovereign, regulated, government, hybrid, or on-premises deployment environments.

Experience with AI evaluation, model observability, inference optimization, capacity planning, FinOps, or cost governance.

Experience leading product engineering across multiple locations.