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

• *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

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