Engineering Manager, Autonomy

True Anomaly•Long Beach, CA

2d•$205,000 - $315,000•Onsite

About The Position

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.

Requirements

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
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
Demonstrated track record of building, growing, and developing high-performing engineering teams including hiring, performance management, and career development
Proven ability to lead through influence, manage stakeholder expectations, drive execution in ambiguous environments, and deliver results through others
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)
Experience with real-time planning systems, resource-constrained deployment, or aerospace applications where autonomy operates under strict compute, latency, and power constraints
Exceptional written and verbal communication skills with ability to influence senior leadership, translate between technical and non-technical audiences, and represent the team effectively
Ability to translate organizational objectives into team strategy, prioritize competing demands, and make trade-offs that balance technical excellence with delivery
Track record of defining processes, establishing team norms, and driving execution excellence in fast-paced environments
Strong cross-functional collaboration skills with ability to build relationships, resolve conflicts, and drive consensus across hardware, software, and trajectory planning teams
U.S. Citizen and eligible for government security clearance

Nice To Haves

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

Responsibilities

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)