Technical Program Manager

Responsibilities

• Assist in planning, coordinating, and tracking aerospace and defense programs from initiation through delivery
• Track and flow down customer and program requirements to engineering and manufacturing teams
• Collaborate with engineering, manufacturing, production, quality, and business operations to align cost, schedule, and technical performance
• Support customer meetings, prepare status reports, and ensure timely delivery of contractual deliverables (SOW, CDRLs, SDRLs)
• Monitor program schedules, track progress against milestones, and support cost reporting
• Identify risks and issues and assist in developing mitigation plans
• Maintain accurate records, action item trackers, and program documentation ensuring compliance with ITAR, DFARS, and aerospace quality standards
• Prepare dashboards, KPIs, and performance metrics for internal leadership and customer review

Requirements

• Bachelor's degree in Aerospace Engineering, Mechanical Engineering, or related field
• Minimum of 3 years of experience within the A&D industry
• Project management experience including requirements decomposition, cost estimating, and risk mitigation
• Technical background in A&D programs including familiarity with structural analysis tools and aircraft systems architectures
• Knowledge of aircraft structures, design, analysis, manufacturing, and qualification
• Experience with fast-iteration hardware-prototyping programs
• Ability to lawfully access information subject to US export controls
• Ability to obtain and maintain a DoD Security Clearance

Preferred Qualifications

• Advanced degree in Aerospace or Mechanical Engineering
• 5 or more years of experience within the A&D industry
• Knowledge of additive manufacturing applications and/or munition weapon systems
• Previous experience in program leadership positions such as Chief Engineer or IPT Lead
• Active DoD Security Clearance

About the Company

Divergent is a technology company that has architected, invented, built, and commercialized an end-to-end factory system called the Divergent Adaptive Production System (DAPS) that uses machine learning to optimally engineer, additively manufacture, and flexibly assemble complex integrated vehicle structures.