Artificial Intelligence Engineer
FOUND | San Francisco, California, United States | 1mo ago
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Original posting (closed) below
full-time | hybrid | lead
skills: agent architectures, llm systems, rag pipelines, retrieval, grounding, orchestration, data ingestion, full-stack, ai infrastructure, distributed systems, mlops, devops, ci/cd, docker, kubernetes
Founding Engineer (AI Agents / Applied AI)
📍 San Francisco Bay Area
We’re partnering with an early-stage company building agentic AI systems for complex, real-world operations — turning fragmented, messy data into instant, reliable intelligence that enables AI to reason and act in high-stakes environments.
This is a true 0→1 founding engineer role, ideal for someone who wants to define the technical foundation from the ground up, not inherit it. You’ll work directly with the founders to design and ship production-grade systems that transform real-world workflows at scale.
What You’ll Do
- Design and build multi-agent systems that reason across messy, real-world data
- Own end-to-end AI pipelines (data → retrieval → orchestration → output)
- Develop evaluation frameworks, benchmarks, and quality loops to ensure reliability
- Build and scale data ingestion + retrieval infrastructure
- Ship full-stack product features in close collaboration with users
- Help define technical architecture, product direction, and engineering culture
What We’re Looking For
- Proven startup experience — comfortable with ambiguity, speed, and ownership
- Experience shipping production-grade AI systems (not just experimentation)
- Strong hands-on experience with:
- Agent architectures / LLM systems / RAG pipelines
- Retrieval, grounding, and orchestration
- Builder mentality — bias for action and shipping
- Ability to operate full-stack and own systems end-to-end
- Strong data instincts — experience working with messy, real-world datasets
Nice to Have
- Experience with evals frameworks and AI quality measurement
- Background in AI infrastructure or distributed systems
- Exposure to automotive, logistics, or other physical-world systems
- MLOps / DevOps experience (CI/CD, Docker, Kubernetes)
- Former founder or early employee at a startup
Why This Role
- Define the core AI systems of the company from the ground up
- Work on problems where AI meets the physical world
- High ownership, high impact — your work ships immediately
- Small, sharp team operating at the frontier
Benefits
equity · health insurance
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