DescriptionRole Overview We are seeking a
Chief Software Architect to serve as the technical lead and systems-level architect for our spacecraft autonomy stack.
This role will define and own the
end-to-end software architecture for autonomy capabilities supporting SDA and ISAM missions:
- Multi-sensor perception and world modeling
- Estimation and relative navigation support for ISAM/RPO missions
- Data pipelines (synthetic + real)
- Embedded deployment to ground station infrastructure, as well as flight/edge hardware
- Government-ready security posture and delivery workflows
- Operational reliability and safety engineering
You will lead a team of engineers spanning
Computer Vision, Full Stack, DevSecOps/Platform, Mod/Sim, and Embedded/Edge deployment, while working closely with company leadership, mission/operations teams, and hardware engineers.
This is a role for someone who wants to architect autonomy that flies - not just publish papers or create prototypes that never leave the lab.
What You'll Own 1) Architecture of the Autonomy Stack (Core Mission) - Define and maintain the end-to-end architecture for a production-grade spacecraft autonomy stack, spanning:
- perception + sensor ingest (EO/IR, multi-camera, star trackers, etc.)
- calibration, time-sync, and sensor health monitoring
- world modeling / representation (relative state, scene understanding, object modeling)
- state estimation interfaces (relative navigation, uncertainty propagation)
- decision & autonomy interfaces (planning hooks, constraints, safety gating)
- fault detection, fallback modes, and confidence-driven behavior switching
- Build scalable, modular designs that transition cleanly from:
- R&D prototypes → validated algorithms → flight/edge-capable products → mission operations
- including clear separation between:
- offline training/evaluation pipelines
- on-orbit/edge inference pipelines
- mission operations tooling
- Establish rigorous interface contracts and architectural guardrails so autonomy capabilities remain:
- reliable
- testable
- upgradeable
- safe to deploy into mission environments (especially for ISAM / RPOD scenarios)
2) Autonomy Software Engineering Excellence - Establish patterns for high-reliability autonomy software:
- modular architectures, clear interfaces, versioning
- deterministic execution where needed
- fault detection, fallback modes, and observability
- Implement rigorous engineering practices without slowing innovation.
3) Deployment Across Cloud + Edge / Embedded Hardware - Drive design decisions across the entire compute surface area:
- cloud data pipelines and model training
- simulation environments and evaluation infrastructure
- embedded inference on real hardware (e.g., GPU edge devices / flight-relevant compute)
- Ensure production performance in real constraints:
- latency, memory, power, bandwidth, thermal constraints
- repeatability, robustness, recoverability
4) System Reliability, Safety, and Security - Work with DevSecOps to ensure architecture supports:
- secure builds, controlled release pipelines
- Government security requirements, traceability, auditability
- secure deployment into customer/government environments CUI up to TS levels
- Design for safety in autonomy contexts:
- bounded behaviors
- explicit failure modes
- confidence estimation and gating
5) Technical Leadership + Team Development - Lead and mentor a multidisciplinary autonomy software team (~10+ engineers in year 1, and multiple teams in year 2)
- Conduct design reviews, set coding standards, define architecture guardrails
- Help recruit top-tier engineers and develop internal technical leadership
6) Research Awareness → Practical Capability - Stay current on the autonomy and perception research landscape:
- CV foundation models, pose estimation, multi-view geometry
- neural implicit representations, 3D reconstruction
- tracking/filtering methods, uncertainty quantification
- Translate research into deployable product capability:
- evaluate, prototype, validate, productize
Responsibilities - Own perception stack architecture across software layers and teams
- Drive end-to-end technical strategy, with clear tradeoffs and rationale
- Create architecture artifacts:
- system design documents, interface contracts, data schemas
- "golden path" workflows for training → evaluation → deployment
- Lead design reviews and ensure consistent implementation across teams
- Enable continuous improvement in performance, scalability, and reliability
- Partner with hardware teams to ensure:
- deployment feasibility
- sensor-to-model integration integrity
- testability and validation strategy
- Communicate architecture decisions clearly to:
- leadership
- program/customer stakeholders
- government partners
Requirements Required Qualifications - 10+ years of professional software engineering experience, with a strong emphasis on software architecture and design.
- Expert knowledge of computer vision and machine learning with hands-on experience developing production-grade systems.
- Demonstrated experience in developing systems for robotics or autonomous vehicles.
- Proficiency in Python and C++, with demonstrated ability to guide technical teams in software development processes.
- Experience with leading cross-functional teams in the development of complex systems.
- Familiarity with GPU-based programming (CUDA) or leading-edge methodologies in computer vision.
- Strong problem-solving skills and a thorough understanding of software performance optimization techniques.
- Ability and willingness to work on-site in Sausalito, CA.
- U.S. citizenship due to ITAR export-control restrictions; only U.S. citizens are eligible for this position.
Preferred Qualifications - Active U.S. Security Clearance
- Demonstrated experience in developing space systems.
- Hands-on experience with cloud-native architecture and integration processes.
- Strong network of industry contacts and thought leadership within the software development community.
- Strong network of highly capable engineers with interest on tackling the hardest problems in space.
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