Lead Product Engineering

About the role

Inception42, a G42 company, is building AI-powered products and acts as the core intelligence layer of the G42 ecosystem. It is looking for a Product Engineering Lead to own engineering execution for an assigned product or major platform area, turning product priorities into production-ready software and helping the squad deliver predictably and with high quality. The role combines technical leadership, team development and delivery accountability.

Key responsibilities

• Own engineering execution for an assigned product or platform area, including planning, development, release and production support.
• Lead and coach a product-engineering squad, setting clear expectations for quality, ownership and delivery.
• Turn prioritized requirements and acceptance criteria into a refined engineering backlog, estimates, sprint goals and release plans.
• Guide architecture and implementation across services, APIs, integrations, user workflows and reusable platform capabilities.
• Partner with Product and Data & AI to turn prototypes and requirements into usable, secure, observable production features.
• Make sure code reviews, automated testing, CI/CD, release readiness, observability and incident response are part of team execution.
• Own engineering risks, technical debt, product reliability, defects and performance improvements.
• Resolve cross-team dependencies and contribute reusable capabilities to shared platforms.
• Track sprint and release outcomes, delivery predictability and quality, and surface blockers and trade-offs early.

Required profile

• Experience leading software engineers to deliver and operate a production product or major platform area.
• Experience owning engineering backlogs, sprint execution, releases and production readiness.
• Track record of coaching engineers and establishing technical ownership and engineering standards.
• Clear communication with product, engineering, AI, security and delivery stakeholders.

Required skills

• Architecture, system design, code review, debugging and production operations.
• APIs, distributed systems, cloud platforms, integrations, security and observability.
• Nice to have: shipping AI-powered products, agent platforms, copilots, workflow systems or developer platforms; exposure to RAG, AI evaluation, grounding, safety, model observability, latency or inference cost management; experience with sovereign, regulated, hybrid or on-premises deployments.

What we offer

• An open, diverse and inclusive culture with a global vision.
• Learning and development opportunities through structured training programs and high-tech projects.
• A competitive remuneration package with healthcare, education support, leave benefits and more.