[Hiring] Autonomy Engineer - Planning & Guidance @Shearwater Aerospace

Role Description

You'll join as a founding engineer on our autonomy stack, inheriting significant prior work and taking full ownership of where it goes next. Working with our CTO, you'll own the autonomy and guidance layer — the algorithms and systems that translate vehicle capabilities, environmental data, and mission objectives into optimal, adaptive flight behavior.

• Extend and harden our route planning and optimization engine — multi-objective, constraint-aware, weather-integrated
• Build real-time guidance logic that adapts plans as conditions evolve (wind shifts, airspace changes, degraded vehicle state)
• Define how weather intelligence translates into actionable flight decisions
• Design planning abstractions that bridge high-level mission objectives and executable vehicle commands
• Own the interface between the planning stack and simulation — ensuring plans are validated against physical reality before they execute on real aircraft

Qualifications

• You've built planners that work outside the lab.
• You know the gap between an algorithm that works on a benchmark and one that holds up under real-world uncertainty, changing constraints, and edge cases.
• Your code is production-grade, not research-grade.
• Strong software engineering is non-negotiable.
• You reason clearly about trade-offs under uncertainty.
• You understand the physics well enough to constrain the planner correctly.
• You're comfortable with ambiguity.

Requirements

• Demonstrated experience with path planning and trajectory optimization — graph-based, sampling-based (RRT/RRT*), or direct optimization methods
• Strong understanding of constrained and multi-objective optimization
• Experience building planners that operate under uncertainty and dynamic constraints
• Familiarity with how environmental data (weather, terrain, airspace) integrates into planning problems
• Strong C++ and/or Python — you write code others want to maintain and extend
• Ability to design planning systems as clean, testable, well-interfaced software — not just algorithmic prototypes
• Experience with performance-sensitive systems where planning latency matters
• Working knowledge of flight mechanics sufficient to reason about vehicle constraints
• Experience with UAV systems, autonomous vehicles, or aerospace applications is a strong plus
• Familiarity with meteorological data and how atmospheric conditions affect flight planning is a bonus
• Comfortable with cloud infrastructure (GCP preferred), Docker, Git

Benefits

• Equity ownership – You're building foundational systems. You should own a meaningful piece of what we're creating.
• Architectural influence – You'll shape the planning architecture alongside the CTO as we push toward production-grade autonomy.
• Hybrid flexibility – Work where you're most productive.
• Direct impact – Your algorithms run onboard aircraft making real flight decisions.