/roles — ROLE_403
Founding Engineer
Very early startup building AI assistants in wearable glasses for technicians at data centers, power grids, and aerospace sites
The role
- COMP
- $170K - $230K
- EQUITY
- 2 - 3%
- LOCATION
- San Francisco
- WORKPLACE
- On-site
- EXPERIENCE
- 1 - 4 years
- VISA
- None, Visa transfers
- STACK
- Python, TypeScript, AWS, GCP, PostgreSQL, Docker, React, REST API, C/C++, Rust
- INDUSTRY
- AI, Hardware, Robotics, Enterprise, Defense, B2B
The company
Wearable AI company putting real-time audio and visual assistance on smart eyewear to guide workers through complex industrial assembly and inspection work.
- STAGE
- Series A-stage
- FUNDING
- $5M raised
- TEAM
- founding team of <10
- FOUNDED
- 2026
JD — the work
About the role
As one of the first hires on a tiny founding team, you would build the full product around an agentic vision-language model that guides industrial technicians through complex work via smart glasses. The work is weighted to backend systems and applied AI but also spans device integration, evals, internal tooling, go-to-market input, and hiring. It suits a scrappy generalist who has already shipped agentic or multimodal AI to real users. The role is on-site in San Francisco.
What you'll do
- Own the product around the core vision-language agent (database, storage, APIs, app) and take it from prototype into production use
- Fit the multi-step, tool-using visual reasoning loop into customer workflows like data center procedures, inspections, and field service
- Co-own evals and the data feedback loop with the team's AI engineer, logging failures and raising quality each release
- Create internal tooling that automates company workflows with AI, and make build-versus-buy calls
- Help pick the next target customers across data center, aerospace, and energy
- Help hire and ramp up the engineers who join next
What they're looking for
- 1 to 4 years of software engineering after graduation, ideally including early-stage startups
- Shipped real products as a founding engineer or very early startup hire
- Backend-heavy full-stack range: you've built data stores, APIs, and app layers on stacks like GCP, AWS, Railway, or Supabase
- Deployed integrations between software and hardware such as drones, IoT devices, cameras, robots, or wearables
- Comfort writing and debugging low-level C, C++, or Rust, including profiling, memory and power limits, and cross-compilation
- Constant hands-on use of the newest AI tools, with scrappy, independent judgment
Nice to have
- Agentic or real-time multimodal pipelines: on-device media capture, low-latency transport, fast model serving
- Edge inference, AR or wearable AI, computer vision, video or audio streaming, robotics, or autonomous driving
- Embedded Linux, RTOS, device SDKs, or firmware, including evaluating camera and sensor hardware
- On-prem or air-gapped deployments for aerospace, defense, or critical infrastructure