AI Engineer (Agentic Systems / Computer Vision / Industrial AI)

Location: Austin, TX or Zurich (Remote flexible)

Compensation: $200,000 – $240,000 + Equity (1–1.5%)

Type: Full-Time

The Opportunity

We’re building AI systems that operate in the real world — not just in notebooks.

This team is focused on agent-driven platforms that interpret and act on physical-world data — video streams, sensor data, industrial signals — to power decision-making across operations, maintenance, and planning.

If you’ve built production AI systems and want to work on problems where data is messy, environments are unpredictable, and the stakes are real, this is that kind of role.

What You’ll Work On

You’ll help design and ship end-to-end AI systems that combine agents, multimodal data, and real-world constraints.

Build agent runtimes and orchestration systems across multiple domains (vision quality, predictive maintenance, operations planning)
Develop multimodal pipelines (video, time-series, sensor data) using computer vision and signal processing techniques
Design context systems (ontology, knowledge graph, memory layers) to ground decision-making in real-world environments
Create decision surfaces: dashboards, alerts, workflows, and audit trails used by operators
Integrate with enterprise systems (ERP, CMMS, WMS, PLCs) and unify complex schemas
Own systems from data ingestion → model serving → backend → user interface

What You’ve Done

Built and shipped production AI systems (3+ years, ideally 5+)
Delivered agentic systems with orchestration, tool use, memory/state, and human-in-the-loop workflows
Worked with real-world data at scale (video streams, IoT, sensor data, telemetry)
Built multimodal pipelines (vision + structured data)
Shipped 0 → 1 products, ideally at a VC-backed startup
Designed systems that handle noise, latency, drift, and imperfect data

What You Bring

Strong backend engineering skills (Python, TypeScript, FastAPI)
Experience with computer vision (OpenCV, YOLO, segmentation, etc.)
Familiarity with streaming/data pipelines and real-time systems
Experience integrating with enterprise platforms (ERP, CMMS, WMS, industrial systems)
Systems mindset: you think about reliability, cost, failure modes, and scale

Nice to Have

Background in robotics, autonomous systems, or industrial environments
Experience with knowledge graphs / ontologies
Built platforms for enterprise customers at scale

Who You Are

You’ve taken AI systems from idea → production → real-world use
You’re comfortable working autonomously in high-ownership environments
You care about execution, not just experimentation
You’re energized by solving messy, real-world problems

Why This Role

Work on real-world AI systems, not theoretical models
High ownership, small team, fast-moving environment
Direct impact on how AI interacts with physical systems and operations
Competitive comp + meaningful equity

AI Engineer (Agentic Systems / Computer Vision / Industrial AI)

Benefits