Level

Unstructured

AI Engineer - Public Sector

Unstructured is hiring an AI Engineer - Public Sector for a remote role. Level rates it ; you can apply on Unstructured.

Level's read on this job

  • On Level's scale, this AI engineer role is Builds AI ●●●●: the job is building AI systems.
  • This is listed as a remote role.
  • The posting mentions LangChain, LangGraph and CrewAI among its tools and skills.
  • Level classes it as a mid-level role.
  • Unstructured has 4 other open roles on Level.

AI in this role

Build and ship production-grade RAG and agentic AI systems for government and military clients using Python and AWS.

langchainlanggraphcrewaidspybedrockpineconeweaviatepgvectorsagemakerdatabrickspythonaws
ragai-agentsfine-tuningai-evaluationcomputer-visionnlpagentic-workflowsmultimodal-data-processingllmsmachine-learning

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.


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 & 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.

 
  • 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.

Must-Haves

  • 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.

Nice-to-Haves

  • 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.

Your Technical Toolkit

  • 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.


Why You'll Love It Here

 

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.

How we rate this

AI Engineer - Public Sector at Unstructured rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGAI agentsFine-tuningAI EvaluationComputer visionNLPAgentic WorkflowsMultimodal Data Processing

Also common in AI engineer jobs at this level

Pay

Typical AI engineer job
$185k

This posting doesn't list pay. Use the typical AI engineer figure when pay comes up. See AI engineer jobs

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. How do you decide when an AI agent can act on its own versus asking for approval first?
  3. Walk me through fine-tuning a model: what data did you use, and how did you check the result?
  4. How do you decide that one model's output is better than another's for a given task?
  5. Walk me through a computer vision problem you solved, from raw data to a deployed model.

Adapt your resume

  • List these exact terms on your resume: RAG, AI agents, Fine-tuning, AI Evaluation, and Computer vision. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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