AI-First Engineering Program Manager — Scale 110-Person ART

Leidos

Gaithersburg (MD)

Hybrid

USD 150,000 - 237,000

Full time

7 days ago
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Job summary

Leidos is seeking an Engineering Program Manager (EPM) to lead the Air Traffic Business Area across a 110-person ART, directing 4–6 People Managers and shaping workforce design, talent strategy, and staffing for the L-CAP platform.

This hybrid role requires US citizenship and the ability to obtain Public Trust clearance, with collaboration across RTE and Product Manager on capacity and budget to deliver mission-critical software with AI-first practices.

Qualifications

  • Bachelor’s degree in engineering or related field.
  • 8+ years of engineering management experience.
  • 3+ years as a second-line manager (managing managers).
  • Experience building, scaling, and retaining engineering organizations of 75+ personnel in a matrixed environment.
  • Workforce planning, headcount forecasting, and organizational design.
  • Engineering talent acquisition governance including requisition strategy and interview processes.
  • Performance management at scale including calibration and compensation planning.
  • Ability to obtain and maintain a Public Trust clearance; US citizenship required.

Responsibilities

  • Serve as second-line engineering manager for an ART of ~110 personnel, directly managing 4–6 People Managers who lead engineering teams.
  • Own workforce planning and organizational design for the ART including team structure, headcount allocation, and skill mix optimization.
  • Drive engineering staffing decisions including hiring priorities, requisition development, and candidate selection governance.
  • Manage engineering talent pipeline ensuring the ART maintains adequate bench strength, succession depth, and critical-skill coverage.
  • Oversee career development strategy for engineering managers, ensuring People Managers are equipped to grow and retain their teams.
  • Govern performance management across the ART — calibrate ratings, align recognition, and ensure equitable evaluation standards.
  • Make cross-team resource allocation and rotation decisions to balance workload, develop talent, and address skill gaps.
  • Partner with the RTE and ART Product Manager on capacity planning, ensuring staffing aligns with delivery priorities.
  • Own engineering headcount budget and labor forecasting for the ART, coordinating with program finance on variance and projections.
  • Drive retention strategy including compensation alignment, engagement initiatives, and attrition risk mitigation.
  • Manage organizational change including team restructuring, role transitions, and onboarding/offboarding of engineering personnel.
  • Align engineering workforce composition with modernization priorities ensuring critical skill sets are developed and retained as legacy expertise transitions to cloud-native competencies.
  • Develop workforce transition plans supporting engineering personnel reskilling from legacy ATC systems to modern distributed service architectures.
  • Coordinate engineering resource strategy across ART boundaries ensuring program-wide workforce balance and avoiding single-point-of-failure dependencies.
  • Champion an AI-first engineering culture by identifying and applying AI-assisted development capabilities, automation, and emerging software engineering practices that improve developer productivity, code quality, testing, and delivery.

Skills

Leadership
Strategic planning
Workforce planning
Hiring governance
Performance management
Talent development
Budgeting
Stakeholder management
AI mindset
Public Trust readiness

Education

Bachelor’s degree

Tools

SAFe
Agile

Job description

Leidos is seeking an Engineering Program Manager (EPM) to lead the Air Traffic Business Area across a 110-person ART, directing 4–6 People Managers and shaping workforce design, talent strategy, and staffing for the L-CAP platform.

This hybrid role requires US citizenship and the ability to obtain Public Trust clearance, with collaboration across RTE and Product Manager on capacity and budget to deliver mission-critical software with AI-first practices.

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