Leads software integrations and deployments of autonomous orchestration platform with customer systems, building adapters for vehicles, sensors, and C2 tools. Requires 3+ years experience in Python/C++, Linux, networking, and customer-facing technical work with up to 50% travel.
Salary not listed
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About the role
Key Responsibilities
Software Integration & Deployment
Build adapters and translation layers that connect our orchestration platform to diverse autonomous vehicle control protocols and APIs (MAVLink, custom vehicle APIs, etc.)
Develop interfaces for new sensors and payloads, integrating their data streams into our world model
Create integrations with third-party C2 systems (ATAK, TAK Server, etc.) and other software platforms in the autonomy stack
Map high-level orchestration tasks to platform-specific behaviors and commands for each vehicle type
Transform and integrate environmental data from various sources into our common data representation
Deploy and configure ML models in operational environments
Design and implement custom network configurations for multi-domain connectivity, handling degraded/intermittent links, secure networks (VPNs, firewalls), and air-ground-sea communication scenarios
Customer & Partner Technical Leadership
Serve as technical liaison between customers/partners and internal engineering teams
Lead on-site integration efforts at partner facilities (vehicle manufacturers, sensor providers, component suppliers)
Conduct technical demonstrations and training sessions for customers and operators
Translate operational requirements and field feedback into actionable product improvements
Support pre-sales technical discussions and scoping for customer engagements
Validate partner platforms and third-party integrations in operational settings
Platform Contributions
Build shared libraries and reusable integration components that accelerate future deployments
Develop deployment tooling and automation for software delivery in secure, constrained environments
Extend our behavior library with new capabilities based on platform-specific features
Contribute bug fixes and improvements affecting customer deployments
Document integration patterns and best practices
Funnel product requirements from field learnings back to core engineering and product teams
Field Operations Support
Execute system validation, troubleshooting, and performance optimization in real-world environments
Provide technical support during live demonstrations and operational deployments
Collect and analyze system performance data, integration issues, and failure modes
Develop deployment documentation and troubleshooting guides
Debug integration issues discovered during field testing
Required Qualifications
3+ years of software engineering experience building integrations, APIs, or distributed systems
Bachelor's degree in Computer Science, Software Engineering, Electrical Engineering, Robotics, or related field (or equivalent hands-on experience)
Strong proficiency in Python and/or C++ for building integrations, adapters, and automation
Experience with networked systems and protocols (TCP/IP, UDP, multicast, routing, subnetting)
Advanced Linux proficiency (command line, scripting, debugging, remote system administration)
Experience integrating with external APIs, protocols, or hardware systems
Proven ability to understand complex technical systems and build translation/adapter layers
Strong debugging and troubleshooting skills across software boundaries
Professional communication skills for engaging customers, partners, and engineering teams
Comfortable with 50% travel to customer sites, partner facilities, test ranges, and remote locations
Preferred Qualifications
Experience with autonomous systems, robotics, or unmanned vehicles (UAS, UGV, USV, UUV)
Hands-on experience with vehicle control protocols (MAVLink, ROS/ROS2, custom vehicle APIs)
DevSecOps experience deploying software in secure, constrained, or classified environments
Experience with tactical communications systems and C2 software (ATAK, TAK Server, Link 16, etc.)
Knowledge of ML model deployment and inference optimization
Background in RF communications, link budgets, or connectivity troubleshooting
Experience with embedded systems, microcontrollers, or firmware interfaces
Familiarity with sensor integration (cameras, LIDAR, radar, EO/IR, RF)
Prior forward deployed, field engineering, or customer-facing technical role experience
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