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Unstructured is defining the standard for enterprise data transformation in the age of LLMs and generative AI. In just two years, we've raised over $65M from world-class investors, including Menlo Ventures, Bain Capital, Databricks, NVIDIA, Microsoft, and IBM.
Our open-source toolkit has been downloaded 97M+ times and is used by 90% of the Fortune 1000. We power production AI workflows across commercial and federal sectors - transforming PDFs, HTML, Word docs, images, emails, and more into AI-ready data pipelines that scale.
We're not just building tools; we're building the backbone of generative AI and the infrastructure that unlocks intelligence across industries.
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.
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.
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.
Technical Resourcefulness: You are comfortable working in restricted or air-gapped environments. When commercial APIs aren’t an option, you have the expertise to deploy, fine-tune, and optimize open-source models to achieve the mission objective.
Autonomous Problem Solving: You can take a high-level government requirement and translate it into a technical roadmap. You don't require constant oversight to identify the right tool for a job, whether it’s a specific vector database or a custom multimodal pipeline.
A "Generalist" Mindset: While you specialize in AI, you understand the full stack. You are as comfortable discussing embedding strategies as you are configuring AWS GovCloud infrastructure or debugging a FastAPI endpoint.
Proven experience deploying Production RAG pipelines against real-world, messy datasets.
Deep expertise in Agentic system design (tool-use, multi-agent orchestration).
Strong Python engineering skills-writing clean, scalable, and maintainable code
Experience operating within AWS/GovCloud environments.
Experience fine-tuning NLP or object detection models.
Familiarity with LLM evaluation frameworks (hallucination detection, drift monitoring).
Knowledge of government security standards and working in different classification environments and on-prem
Security Clearance: Existing Secret/TS clearance or eligibility is a significant plus.
Languages: Python (expert-level), SQL
LLM & Agentic Frameworks: LangChain, LangGraph, CrewAI, or similar orchestration frameworks
RAG Stack: Retrieval with vector databases (Pinecone, Weaviate, Chroma, pgvector), graph databases (Neo4J), Elasticsearch, BM25, and Sentence-Transformers; NLP enrichment with spaCy, GLiNER, and Transformers; optimization using embedding models, reranking pipelines, and DSPy
Evaluation & Observability: RAGAS, DeepEval, Arize Phoenix, and synthetic annotations
Cloud & Infrastructure: AWS, SageMaker, Bedrock, S3, Lambda, Docker, and FastAPI
Data Processing: Complex pipelines for unstructured and multimodal data, including PDFs, scanned documents, images, and audio.
You'll be surrounded by smart, kind, low-ego people who genuinely enjoy building together. We invest in our team with company offsites, best-in-tech swag, and the tools you need to do your best work, wherever you're based.
We support you holistically, not just at work. From medical, dental, and vision coverage effective the 1st of the month following your start date, life and disability insurance, unlimited PTO, and flexible parental leave, to a 401(k) with company match, equity, a $500 work from home stipend, $70/month internet reimbursement, and team/company offsites throughout the year - we want you focused on building, growing, and staying energized for the long haul.
If you're excited about what we're building, we'd love to meet you.
Unstructured is proud to be an Equal Opportunity Employer. We're committed to building a diverse team and an inclusive culture where everyone can do their best work. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other characteristic protected by applicable law.