AI Technical Program Manager

Role Name: AI Technical Program Manager
Location: Boston, MA   Onsite / Local Needed
Duration: 12+ Months Contract with Possible Extension
Visa: 
Federal Check: Required
Interview: 2 Video Interviews
Pay Rate: $80-90/hr on 1099 
About the Role

We are seeking a highly technical AI Technical Program Manager (TPM) to join a Physical AI / Robotics team. This role will manage complex programs involving hardware development, lab operations, engineering workstreams, validation campaigns, and technical dependencies.

The ideal candidate must be genuinely technical and capable of participating in hardware design reviews, understanding engineering discussions, identifying technical risks, and translating complex technical information into clear program-level decisions, risks, and actions.

This is not a coordination-only TPM role. The candidate should be comfortable working in ambiguous, greenfield, fast-paced R&D environments and building program structure and processes from the ground up.

Key Responsibilities

Program Planning & Execution

• Own the integrated program plan covering hardware builds, lab operations, validation campaigns, and engineering milestones.

• Manage cross-team dependencies, risks, milestones, and schedules.

• Establish program cadences including sprint planning, milestone reviews, risk reviews, and cross-team syncs.

• Track action items, decisions, commitments, and deliverables across multiple workstreams.

• Drive accountability and ensure timely completion of commitments.

Risk & Decision Management

• Identify technical, schedule, and resource risks proactively and develop mitigation strategies.

• Establish appropriate escalation and decision-making pathways.

• Build and maintain program dashboards providing leadership visibility into status, risks, blockers, and dependencies.

• Facilitate technical tradeoff and prioritization discussions.

• Document key decisions and ensure clear ownership and follow-through.

Cross-Team Alignment

• Act as the bridge between onsite lab teams, engineering teams, and organizational stakeholders.

• Translate technical status into program-level communication for leadership.

• Communicate program status, risks, dependencies, and decisions to engineering leadership.

• Coordinate with Supply Chain, Facilities, IT, and external engineering partners.

• Manage scope changes, shifting priorities, and new requirements.

Process & Tooling

• Build program management processes from scratch for a fast-moving R&D environment.

• Own program tracking tools such as Jira, Confluence, Asana, or similar platforms.

• Develop and maintain RACI frameworks for major workstreams.

• Establish lightweight processes that provide structure without unnecessary enterprise overhead.

Required Qualifications

• Bachelor's degree in Engineering, Computer Science, or related technical field.

• 7+ years of Technical Program Management experience.

• 3+ years managing programs involving hardware development, physical systems, or robotics.

• Strong technical understanding of hardware build processes, testing, validation, and engineering dependencies.

• Experience managing complex, multi-workstream technical programs.

• Experience working in ambiguous or greenfield environments.

• Demonstrated ability to build program management infrastructure, processes, tools, and cadences from scratch.

• Strong written and verbal communication skills.

• Ability to create status reports, risk registers, decision documents, and executive-level communications.

• Strong risk management, dependency management, stakeholder management, and program execution skills.

Preferred Qualifications

• Experience in Physical AI, Robotics, Autonomous Systems, or Advanced Hardware R&D.

• Experience with hardware development lifecycles, including NPI, EVT, DVT, PVT, prototype builds, and validation.

• Familiarity with Agile methodologies in hardware development environments.

• Experience working at a hyperscaler, frontier AI lab, or high-growth technology company.

• Experience working in fast-paced and highly ambiguous R&D environments.