AI Engineer

CDIT; Massachusetts; On-site; USD 120,000 - 160,000; Full time

Job summary

CDIT is seeking an AI Engineer to design, develop, and deploy ML/NLP solutions supporting NAVSEA signals in Norfolk, VA. You will transform maintenance and logistics data into predictive insights, collaborating with Navy SMEs and program leadership to productionize models in an AWS GovCloud environment.

You will work on supervised, unsupervised, and generative models, implement MLOps, and apply NLP to maintenance narratives and 3M records. A DoD clearance is required.

Qualifications

• 5+ years hands-on experience deploying ML/AI systems in production.
• Expert-level Python and data-science tooling (pandas, NumPy, scikit-learn) with at least one deep-learning framework.
• Experience with LLMs, prompt engineering, RAG, embeddings, and vector search.
• AWS ML services — SageMaker, Bedrock, Lambda, S3, IAM — preferably GovCloud (US).
• Containerized workloads and CI/CD pipelines for ML (Docker, ECS/EKS).
• Strong statistics, evaluation, and experimentation methods.
• Clear communication to non-technical Navy/program stakeholders.
• Active DoD Secret clearance at time of hire.

Responsibilities

• Design and build supervised, unsupervised, and generative AI models against Navy datasets.
• Develop end-to-end ML pipelines: ingestion, feature engineering, training, evaluation, deployment, monitoring.
• Implement MLOps in AWS GovCloud using SageMaker, Bedrock, Step Functions, Lambda, ECS/EKS.
• Apply NLP to unstructured maintenance narratives, CASREPs, and 3M records.
• Collaborate with data engineers on schemas, feature stores, and vector databases.
• Establish model governance: versioning, bias/drift monitoring, evaluation harnesses.
• Document model design and limitations for government review and accreditation.
• Support proposals, demonstrations, and pilots as directed by leadership.

Skills

LLMs

Prompt engineering

RAG

Vector search

Stakeholder comms

Education

Bachelor's degree in Computer Science

Master's or PhD preferred

DoD 8570 / 8140 IAT Level II baseline certification

Tools

Python

PyTorch

TensorFlow

scikit-learn

HuggingFace

AWS SageMaker

Bedrock

Lambda

S3

IAM

Docker

ECS

EKS

CI/CD

Job description

The AI Engineer will design,develop, and deploy machine learning, natural language processing, andgenerative AI solutions supporting the NMMES program at Naval Sea SystemsCommand (NAVSEA) in Norfolk, VA. The role focuses on turning large volumes ofship maintenance, logistics, and readiness data into predictive insights anddecision-support tools that improve fleet availability, reduce unplannedmaintenance, and accelerate work-package planning.

The engineer will work directlywith data scientists, software engineers, Navy subject-matter experts, and CACIprogram leadership to move models from prototype to production within an AWSGovCloud environment. This position requires a blend of hands-on MLengineering, MLOps discipline, and comfort operating in a Defense customerenvironment governed by DoD security and accreditation processes.

Key Responsibilities

• Design and build supervised, unsupervised, andgenerative AI models (including LLM-based RAG pipelines) against Navymaintenance, supply, and equipment-history datasets.
• Develop end-to-end ML pipelines — data ingestion,feature engineering, training, evaluation, deployment, and monitoring — usingPython and modern ML frameworks (PyTorch, TensorFlow, scikit-learn, HuggingFace).
• Implement MLOps practices in AWS GovCloud usingSageMaker, Bedrock, Step Functions, Lambda, and containerized workloads(ECS/EKS).
• Apply NLP techniques (entity extraction,classification, summarization, semantic search) to unstructured maintenancenarratives, casualty reports (CASREPs), and 3M records.
• Collaborate with data engineers to define schemas,feature stores, and vector databases (OpenSearch, pgvector) that supportproduction inference.
• Establish model governance practices: version controlfor models and datasets, bias and drift monitoring, evaluation harnesses, andhuman-in-the-loop feedback loops.
• Document model design, assumptions, and limitations ina manner suitable for Government review, accreditation, and technical exchangemeetings.
• Support proposal, demonstration, and pilot activitiesas directed by CACI and CDIT Solutions leadership.

Required Qualifications

• 5+ years of hands-on experience building and deployingML or AI systems in production.
• Expert-level Python, including data-science tooling(pandas, NumPy, scikit-learn) and at least one deep-learning framework (PyTorchor TensorFlow).
• Demonstrated experience with LLMs, prompt engineering,retrieval-augmented generation (RAG), embeddings, and vector search.
• Working knowledge of AWS ML services — SageMaker,Bedrock, Lambda, S3, and IAM — preferably in GovCloud (US).
• Experience deploying containerized workloads (Docker,ECS, or EKS) and building CI/CD pipelines for ML.Solid grounding in statistics, model evaluation, andexperimentation methodology.
• Ability to communicate technical concepts clearly tonon-technical Navy and program stakeholders.
• Active DoD Secret clearance at time of hire.

Preferred Qualifications

• Prior experience supporting Navy, NAVSEA, or other DoDmaintenance / logistics programs.
• Familiarity with Navy data sources such as NMMES-TR,Maintenance Figure of Merit (MFOM), OARS, or 3M/MDS.
• Experience with responsible-AI frameworks, model cards,and DoD AI ethics principles.
• Exposure to knowledge graphs, ontologies, orgraph-based retrieval.
• TS/SCI clearance.

Education

Bachelor’s degree in ComputerScience, Data Science, Applied Mathematics, Statistics, or a related technicaldiscipline. Master’s or PhD strongly preferred. Additional relevant experiencemay be substituted for degree requirements consistent with contractlabor-category definitions.

Certifications

Required

• DoD 8570 / 8140 IAT Level II baseline certification(e.g., Security+ CE) — required within 6 months of hire if not currently held.

Preferred

• AWS Certified Machine Learning – Specialty
• AWS Certified Solutions Architect – Associate orProfessional
• Certified Ethical Hacker (CEH) or CISSP