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AI/Data Engineer

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Onsite

AI/Data Engineer

Dunedain

AI/Data Engineer

Skills

Google Cloud PlatformSQL QueriesDockerData MiningPythonPostgreSQLNeo4jMachine LearningAIAWSKubernetesNLP / Natural Language ProcessingComplianceAzure

3 months ago

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Important information


Contract type:

Permanent

Location:

Austin, TX, USA

Work mode:

Onsite

Published on:

8 August 2026

What they need


AI/Data Engineer (Full-Time)

Dunedain | Austin, TX

ABOUT US

Dunedain is building the battlefield operating system of the future and fielding it today.

We turn the digital noise of combat and training into a single coherent picture. Our products let operators plan, decide, and act at machine speed, in the fight alongside the autonomous systems maneuvering beside them. Warfighting formations that run our stack gain a living intelligence, one that learns how they fight and grows with them, from fireteam to Corps.

Unlike most military technology vendors, we are not a concept, a slide deck, or hot air. We are not waiting to be told what to build for the future fight. We're a team of former Warfighters and elite developers, scaling aggressively to give the US military and allies the most unfair decision and tempo advantage in human history.

ROLE OVERVIEW

As an AI/Data Engineer, you'll design, build, and optimize the data infrastructure and retrieval pipelines that power our agents. That means owning the vector, graph, and relational stores behind agentic RAG and agentic graph RAG so our systems can pull the right military data and reason over it in context. You'll work with our engineering and product teams to ship reliable data systems and AI that improve decisions and cut the busy work out of defense workflows. Full-time, hybrid in Austin, TX, with travel up to 25%.

KEY RESPONSIBILITIES

  • Design, build, and optimize data pipelines and agentic RAG / agentic graph RAG systems for military data retrieval and contextual generation.

  • Build and maintain the data backbone: vector databases, graph stores, relational schemas, and indexing strategies that stay fast and relevant at scale.

  • Experiment with NLP, NLU, and NLG techniques to push the capability and performance of our AI products.

  • Work with software engineers to get data pipelines and models into production, with scalability, reliability, and operational use demands.

  • Provide technical leadership across the product development process.

REQUIRED SKILLS AND EXPERIENCE

  • Data Infrastructure & RAG: Hands-on experience with RAG systems (ideally agentic and graph-based), vector/graph databases, data modeling, and solid NLP fundamentals. Experience with language model fine-tuning is a plus.

  • Programming: Strong Python and SQL, with real proficiency in Neo4j, Qdrant (or similar vector/graph stores), and relational databases (PostgreSQL or equivalent). Comfortable with CRUD operations and schema design.

  • Production experience: You've shipped data pipelines and ML systems into production on a cloud platform (AWS, GCP, or Azure) with containerization (Docker, Kubernetes), working with software engineers to integrate them into live applications.

  • Problem-solving: You can drive a project from concept to execution on your own and keep it aligned with the mission and the needs of defense end-users.

  • US Citizenship required, and willingness and eligibility to obtain a US security clearance

PREFERRED QUALIFICATIONS

  • Experience with agentic graph RAG or knowledge-graph-backed retrieval.

  • Military experience.

  • Startup experience, or a track record in fast-moving, agile projects.

  • Familiarity with the defense sector, including the data security and compliance requirements that come with it.

  • Experience building for government or defense users, where the specific workflow matters.

BENEFITS

  • A direct hand in bringing AI to the defense mission, on a small, fast-moving team.

  • Hybrid in Austin, TX or Remote

  • Competitive total compensation of $150,000 - $300,000+ 0.1-0.5% company equity, based on experience.

TO APPLY

Send your resume and a short cover letter. Tell us about your work with agentic RAG, fine-tuning, and NLP, how you solve hard problems, and why you want to build this at Dunedain.

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