The AI Engineer will design, prototype, and deploy RAG pipelines and agentic workflows to process unstructured data for Government and Military clients. Responsibilities include collaborating on architecture and delivering technical reports while ensuring systems are scalable and reliable.
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 Do Day-to-Day
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.
The Ideal Candidate
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 Join Us
Opportunity to work on a dynamic team and work on cutting-edge machine learning projects.
Collaborative and innovative work environment with a focus on learning and growth.
Impactful role in shaping the company's direction and driving innovation in unstructured data processing.
Competitive compensation package, including benefits and stock options.
Similar Jobs
Digital Media • Information Technology • News + Entertainment
Full‑stack .NET developer responsible for writing, maintaining and optimizing code, designing APIs and system architecture, implementing unit/integration tests, supporting deployments, troubleshooting performance issues, and collaborating with QA and stakeholders. May work variable hours including nights/weekends.
Top Skills:
AjaxAngularAsp.NetBootstrapperC#Continuous IntegrationCSSEntity FrameworkGitHTMLIisIocJavaJavaScriptJqueryJSONLinqMvc 5Net Core 2.0Net FrameworkOrmSalesforce Experience CloudSap AbapSQL ServerTfsTypescriptVb.NetVisual StudioWeb ApiXML
Digital Media • Information Technology • News + Entertainment
Design, build, test, and deploy scalable Salesforce solutions across multi-cloud environments using Apex, LWC, Visualforce, declarative tools and integrations (MuleSoft/REST/SOAP). Lead configuration, data modeling, CI/CD, code reviews, troubleshooting, and Agile delivery while mentoring junior engineers and supporting platform governance and long-term architectural alignment.
Top Skills:
ApexCi/CdCopadoCSSFlowsGitHTMLJavaScriptLightning App BuilderLightning Web Components (Lwc)Media CloudMulesoftRest ApisSales CloudSalesforce Experience CloudService CloudSoap ApisSOQLSoslVisualforce
Digital Media • Information Technology • News + Entertainment
Sell Comcast Business solutions to mid-market and enterprise multi-location customers by developing territory strategy, prospecting leads, delivering face-to-face presentations, and managing customer relationships. Collaborate with partners and internal teams to meet financial targets, ensure service excellence, and maintain accurate sales records. Requires knowledge of network design, SDWAN, security, and related networking technologies.
Top Skills:
23)Business Continuity/Disaster RecoveryCustomer Premises Equipment (Cpe)CybersecurityEthernetLanManNetwork SecurityNetworking Protocols (Layers 1SdwanVoipVpnWanWdm
What you need to know about the Chicago Tech Scene
With vibrant neighborhoods, great food and more affordable housing than either coast, Chicago might be the most liveable major tech hub. It is the birthplace of modern commodities and futures trading, a national hub for logistics and commerce, and home to the American Medical Association and the American Bar Association. This diverse blend of industry influences has helped Chicago emerge as a major player in verticals like fintech, biotechnology, legal tech, e-commerce and logistics technology. It’s also a major hiring center for tech companies on both coasts.
Key Facts About Chicago Tech
- Number of Tech Workers: 245,800; 5.2% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: McDonald’s, John Deere, Boeing, Morningstar
- Key Industries: Artificial intelligence, biotechnology, fintech, software, logistics technology
- Funding Landscape: $2.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Pritzker Group Venture Capital, Arch Venture Partners, MATH Venture Partners, Jump Capital, Hyde Park Venture Partners
- Research Centers and Universities: Northwestern University, University of Chicago, University of Illinois Urbana-Champaign, Illinois Institute of Technology, Argonne National Laboratory, Fermi National Accelerator Laboratory
