Lead Engineer, AI & Embedded Systems (Edge / Tactical Systems)

Company: DownTrace AI

DownTrace AI was founded by a Stanford-trained computer scientist and former U.S. Special Forces operator who has firsthand experience with the limitations of current defense technology in real-world environments.

The company exists to solve a specific problem: most modern software assumes constant connectivity, high bandwidth, and cloud dependence—conditions that do not exist in tactical or contested environments. As a result, critical systems often fail when they are needed most.

DownTrace AI is building field-first systems that operate reliably in denied, degraded, and disconnected environments (DDIL). These systems combine:

• Edge-based AI and small, efficient models
• Embedded and device-level computing
• Real-time situational awareness and mapping platforms used by operators in the field
• Simulation and mission-oriented software systems

The company is in early stages but is already positioning itself for work with U.S. government and Tier 1 defense contractors.

This is an opportunity to join at the ground floor, work directly with a founder who understands both the technical and operational problem space, and help build a company designed to deliver practical, deployable systems—not theoretical solutions.

DownTrace AI seeks a Lead Engineer to design and build systems at the intersection of AI, embedded systems, and real-time operational software.

This role is highly hands-on and spans edge inference, embedded development, and full-stack systems. You will be responsible for building systems that function reliably without cloud dependency, integrating with platforms used for mapping, coordination, and real-time decision-making in the field.

You will work directly with the founder and will have significant ownership over architecture, product direction, and technical execution.

A core part of this role involves working with systems used by military and government teams to maintain a shared real-time operational picture, including mapping, communication, and coordination tools.

These platforms typically provide:

• Real-time location tracking and team awareness
• Shared maps, imagery, and overlays
• Secure messaging and data exchange
• Integration with drones, sensors, radios, and edge devices
• Extensible plugin-based architectures

Prior experience with these systems is not required, but candidates should be comfortable working with real-time, distributed, and geospatial systems.

• Architect and build AI-enabled systems for deployment on edge and embedded platforms.
• Develop small, efficient AI models optimized for constrained environments.
• Integrate software with devices such as drones, sensors, radios, and mobile endpoints.
• Build systems that interface with real-time mapping and coordination platforms.
• Develop full-stack infrastructure for device orchestration, data pipelines, and operator interfaces.
• Create simulation environments for testing and validation under realistic conditions.
• Ensure systems function reliably in low-connectivity or offline environments.
• Collaborate directly with leadership and external partners on technical direction and execution.

• Degree in Computer Science, Engineering, or related field, or equivalent practical experience.
• Strong software engineering background across AI/ML, embedded systems, or distributed systems.
• Experience building production systems under real-world constraints.
• Proficiency in Python, C , Go, Rust, or similar languages.
• Ability to design systems that operate independently of cloud infrastructure.
• Strong problem-solving ability and capacity to operate independently.

• Experience with geospatial systems or real-time collaboration platforms.
• Experience integrating hardware or external data sources.
• Familiarity with edge AI optimization techniques.
• Background in defense, robotics, aerospace, or mission-critical systems.

• U.S. citizenship strongly preferred
• Must be eligible to obtain a U.S. security clearance
• Prior clearance is a plus

• Direct impact: You will build systems intended for real-world deployment in high-stakes environments.
• Technical ownership: Significant influence over architecture and product direction.
• Founder access: Work directly with a founder who understands both engineering and operational realities.
• Early-stage upside: Equity and the potential to grow into a foundational leadership role.
• Mission-driven work: Focus on solving problems that conventional software companies do not address.

Submit:

• Resume
• Portfolio or GitHub
• Brief statement of interest

Subject: Lead Engineer Application – DownTrace AI