Senior Technical Project Manager – AI Engineering

Role overview

Project planning and delivery

• Translate business objectives into scopes, milestones, delivery schedules, and quantifiable success metrics.
• Set task ownership, acceptance criteria, estimates, and commitments; track daily progress against baselines.
• Coordinate cross-product dependencies, resource capacity, and priorities; mitigate blockers and govern changes to scope, schedule, and resources.

Technical oversight and quality

• Assess AI/ML feasibility and architecture with engineering leads; challenge unrealistic estimates and unnecessary complexity.
• Evaluate trade-offs in accuracy, latency, operating cost, maintainability, and reliability; identify reusable components and patterns.
• Require rigorous evaluation, benchmarks, statistical targets, production monitoring, failure handling, data security, and human oversight.

Reporting and process

• Verify progress through demonstrations, test results, evaluation reports, and deployment logs; maintain executive visibility into risks and decisions.
• Control scope, document decisions, establish readiness, completion, and release standards, and facilitate planning, risk reviews, and milestone demos.

Required qualifications and experience

• Proven experience as a Technical Project Manager, Technical Program Manager, or Engineering Lead delivering complex software projects.
• Hands-on experience building, testing, or deploying production AI/ML systems beyond basic prompting or API wrappers.
• Experience managing multifaceted plans, cross-functional trade-offs, and on-schedule product delivery.
• Deep knowledge of AI lifecycles, evaluation frameworks, latency/cost trade-offs, and production monitoring.
• Strong communication with engineers and C-suite stakeholders, and a data-driven approach to tracking and problem-solving.

Candidate profile