ashby
AI Engineer - Public Sector
Unstructured
Remote, USA
Full-time
Mid · 3+ years experience
Remote
Discovered 1 weeks ago
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The Mission
At Unstructured, we are obsessed with transforming messy, unstructured data into a format that LLMs can actually use. Our Public Sector team has recently secured several high-impact contracts that demand more than just "off-the-shelf" solutions. We are looking for an AI Engineer who thrives at the intersection of R&D and production-grade software engineering.
You won’t just be building notebook demos; you will be architecting, prototyping, and shipping novel multimodal data processing, RAG, and agentic systems that solve critical problems for Government and Military clients. Your work will bridge the gap between one-off custom builds and a repeatable, scalable product roadmap.
What you'll own and drive
You will be a high-agency individual contributor, owning the lifecycle of AI solutions from initial research to AWS deployment.
50% Building & Shipping: Design and implement production-grade RAG pipelines and agentic workflows using Python. You’ll build systems that handle real-world "messy" data (PDFs, scanned docs, images, full motion video) and ensure they are performant and scalable.
30% Research & Experimentation: Stay at the bleeding edge. You’ll evaluate new models (LLMs, embedding models, object detection), prototype approaches for SBIR/government deliverables, and run experiments to prove what actually works.
20% Strategy & Collaboration: Partner with the team to document architectures, contribute to technical reports for contract deliverables, and participate in pre-sales calls to architect solutions for complex client needs.
What we're looking for
We are looking for a self-directed engineer who excels in high-stakes, ambiguous environments. You are likely a strong fit if your professional background reflects the following:
Systems-First Engineering: You prioritize building reliable, scalable systems over experimental scripts. You have a track record of moving AI models out of notebooks and into production environments where latency, cost, and accuracy are treated as first-class citizens.
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