Engineering Manager, Autonomy

Space is a warfighting domain. True Anomaly seeks those with the talent and ambition to build the technology that secures it. OUR MISSION True Anomaly delivers decisive capabilities for space superiority. We build autonomous spacecraft, advanced payloads, mission software, and space-based interceptors — enabling the U.S. and its Allies to secure the space environment and counter threats from the ultimate high ground. OUR VALUES Be the offset.   We create asymmetric advantages with creativity and ingenuity. What would it take?  We challenge assumptions to deliver ambitious results. It’s the people.  Our team is our competitive advantage and we are better together. 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. RESPONSIBILITIES Technical Oversight & Strategic Contributions 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 Strategic Planning & Execution 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 Team Leadership & People Management 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) QUALIFICATIONS 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 st