Engineering Manager, Autonomy

YOUR MISSION

As Engineering Manager, Autonomy, you will build and lead a team of autonomy engineers who develop multi-agent resource allocation systems and edge-deployed physical AI capabilities for spacecraft operations. You will be responsible for team growth, performance, and delivery while ensuring alignment with the broader autonomy roadmap spanning constellation scheduling, onboard replanning, and distributed coordination. You will translate technical vision into execution, develop talent, and create the processes and culture that enable your team to deliver validated, rugged autonomy systems that operate under compute and latency constraints and evolve through continuous learning. Your primary focus is people leadership, with technical contributions focused on strategic direction, architecture reviews, and maintaining credibility with your team.

• →Provide technical direction on multi-agent coordination architectures, edge deployment strategies, and validation approaches for constrained optimization problems in spacecraft operations
• →Review and approve technical designs for combinatorial optimization algorithms, stochastic planning systems, and distributed coordination protocols
• →Participate in all aspects of a project's development lifecycle, including design, implementation, and verification. Lead the team by example, setting the standard for technical work (approximately 35% of time)
• →Define autonomy standards, explainability requirements, and validation approaches that enable deployment in high-stakes environments
• →Drive technical decisions on compute allocation, edge optimization strategies, and real-time performance trade-offs
• →Maintain technical credibility in operations research, reinforcement learning, and edge AI deployment

• →Define and own the team roadmap in collaboration with autonomy leadership, balancing near-term delivery (flight demonstrations, customer test campaigns) with long-term capability development (continuous learning, end-to-end neural planning)
• →Translate organizational strategy and technical vision into actionable team objectives aligned to customer missions
• →Prioritize work across competing demands: scheduling system maturation, edge autonomy for proximity operations, multi-spacecraft coordination, anomaly detection agents
• →Manage dependencies and coordinate with hardware, trajectory planning, and flight software teams to ensure successful cross-functional delivery
• →Track and communicate team progress, risks, and blockers to leadership and stakeholders with focus on demonstration readiness and customer deliverables
• →Drive continuous improvement in team processes, tools, and workflows to increase velocity from prototype to production-ready systems
• →Work with technical program managers to scope projects, estimate timelines, and commit to deliverables

• →Build, grow, and lead a team of autonomy engineers through recruiting, hiring, onboarding, and retention
• →Provide direct people management including 1-on-1s, performance reviews, goal setting, and career development
• →Foster a culture of technical excellence, rigorous evaluation, and rapid iteration from concept to flight
• →Develop individual contributors into technical leaders through mentorship, coaching, and growth opportunities
• →Manage team dynamics, resolve conflicts, and ensure healthy team communication and collaboration
• →Facilitate knowledge sharing, cross-training, and documentation practices to build team resilience and institutional knowledge
• →Bridge air domain autonomy expertise with space domain constraints (orbital mechanics, communication latency, compute/power budgets)

• Education:Master's degree in computer science, aerospace engineering, robotics, applied mathematics, operations research, or related technical field; Ph.D. or Bachelor's degree with equivalent professional experience also accepted
• Experience:8+ years of experience in autonomous systems, robotics, AI/ML, or aerospace engineering with at least 4 years in people management, leading teams of 4+ engineers
• People Management:Demonstrated track record of building, growing, and developing high-performing engineering teams including hiring, performance management, and career development
• Leadership:Proven ability to lead through influence, manage stakeholder expectations, drive execution in ambiguous environments, and deliver results through others
• Technical Foundation:Strong foundation in autonomous systems with depth in areas such as multi-agent coordination, combinatorial optimization, reinforcement learning, or constrained planning (sufficient to provide technical oversight and credibility)
• Domain Knowledge:Experience with real-time planning systems, resource-constrained deployment, or aerospace applications where autonomy operates under strict compute, latency, and power constraints
• Communication:Exceptional written and verbal communication skills with ability to influence senior leadership, translate between technical and non-technical audiences, and represent the team effectively
• Strategic Thinking:Ability to translate organizational objectives into team strategy, prioritize competing demands, and make trade-offs that balance technical excellence with delivery
• Process & Execution:Track record of defining processes, establishing team norms, and driving execution excellence in fast-paced environments
• Collaboration:Strong cross-functional collaboration skills with ability to build relationships, resolve conflicts, and drive consensus across hardware, software, and trajectory planning teams
• Clearance:U.S. Citizen and eligible for government security clearance

• Experience managing geographically distributed or hybrid teams
• Experience managing teams through full product development lifecycles from early prototypes through operational deployment
• Track record delivering complex, multi-quarter initiatives requiring coordination across multiple teams and hardware/software integration
• Experience with agile methodologies, sprint planning, and iterative delivery in engineering environments
• Background in autonomous aerospace systems: UAVs, spacecraft autonomy, robotic systems, or similar applications
• Deep experience with operations research: mixed-integer programming, constraint satisfaction, graph optimization, auction algorithms, or task allocation
• Background in multi-agent reinforcement learning: MARL, policy learning, reward shaping, credit assignment, or cooperative game theory
• Experience with edge AI deployment: model compression, quantization, inference optimization, embedded ML systems, or real-time neural network execution
• Background in stochastic optimization, robust planning under uncertainty, or Monte Carlo methods for decision-making
• Experience with trajectory optimization, motion planning, or sequential decision-making in constrained environments
• Prior work with hierarchical planning systems, temporal reasoning, or hybrid discrete-continuous optimization
• Background partnering with product management to define requirements and prioritize features based on technical leverage
• Experience with resource planning, capacity modeling, and headcount justification
• Prior work bridging research prototypes (ICAPS/NeurIPS-quality) to production systems with emphasis on scalability and reliability

• Work Location—Successful candidates will be located near Denver, CO or Long Beach, CA.
• Work environment—the work environment; temperature, noise level, inside or outside, or other factors that will affect the person's working conditions while performing the job.
• Physical demands—the physical demands of the job, including bending, sitting, lifting and driving.

This position will be open until it is successfully filled. To submit your application, please follow the directions below.

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