Data Scientist​/AI Engineer in Chesapeake

Job Description Job Description

Carrier Team One (CT1) leads transformative data-driven process improvement and knowledge management initiatives for nuclear aircraft carrier maintenance and modernization. This includes maintenance support for all aircraft carrier availabilities, including Refueling Complex Overhaul (RCOH), Planned Incremental Availability (PIA), Selected Restrictive Availability (SRA), Docking Planned Incremental Availability (DPIA), and Carrier Incremental Availability (CIA). The Senior Data Scientist / AI Engineer serves as the principal technical expert and hands‑on builder for CT1's advanced analytics and artificial intelligence capabilities.

This role directly supports the mission to accelerate capability delivery to the fleet, reclaim decades of obsolescence across alterations, and optimize the expenditure of thousands of man‑days and millions of dollars per availability. CT1 particularly values candidates who combine strong technical capability with exceptional learning agility, intellectual curiosity, and drive to rapidly master complex domains and deliver measurable results. This work builds upon CT1's existing Operations Dashboard and Qlik Sense analytics investments that have already demonstrated $9.3M+ savings and 5,200+ man‑day reductions per project.

This is a senior technical individual‑contributor role (non‑supervisory) requiring deep expertise in modern LLM engineering, production MLOps, and the ability to translate operational Navy requirements into reliable, secure, and measurable AI solutions. The position demands both exceptional technical craftsmanship and strong stakeholder communication skills to brief results and limitations to project superintendents, engineers, senior leadership, and external stakeholders (NAVSEA, PEO, TYCOM).

The primary focus of this position is the design, development, deployment, and continuous improvement of production‑grade Retrieval‑Augmented (RAG) systems, agentic AI workflows, and LLM‑powered analytics tailored to carrier hotwashes (after‑action reviews), project performance data, technical documentation, and operational decision support. The incumbent will leverage and extend platforms including ADVANA, Databricks, AWS Sage Maker, Lang Chain/Lang Graph, and cURL to turn complex, unstructured, and structured naval maintenance data into actionable insights, automated summaries, predictive signals, and natural‑query capabilities.

35% — LLM/RAG Pipeline Architecture, Development & Productionization

20% — Data Engineering, Ingestion & Vector Infrastructure

15% — AI‑Augmented Operational Analytics & Decision Support

10% — MLOps, Evaluation, Monitoring & Responsible AI

10% — Cross‑Functional Collaboration, Validation & Knowledge Transfer

5% — Research, Prototyping & Technology Scanning

5% — Mentorship, Documentation, Compliance & Continuous Improvement

• Expert-level knowledge and hands‑on production experience with modern LLM engineering, RAG architectures, agentic workflows (Lang Graph or strong equivalent), prompt engineering, evaluation frameworks, and grounding/citation techniques.
• Advanced proficiency in Python and the LLM/data ecosystem:
  Lang Chain/Lang Graph (or Llama Index + custom orchestration), vector databases, embedding models, Hugging Face Transformers (as needed), Pandas/Polars, SQL, and Spark/Databricks Delta Lake.
• Strong practical experience deploying and operating ML/AI workloads on cloud platforms, with preference for AWS Sage Maker and/or Databricks; equivalent experience on Azure ML or Google Vertex AI is highly transferable.
• Demonstrated ability to build production data pipelines,…