Description

We are seeking an experiencedSenior Data Scientist to support the Program Executive Office (PEO) Digital portfolio by leading the architecture, design, and implementation of next-generation Agentic AI capabilities for Department of Defense digital modernization initiatives. This individual will serve as the technical lead responsible for developing AI-enabled solutions that operate seamlessly across Microsoft Azure, AWS, Google Cloud Platform (GCP), and on-premises environments while maintaining strict security and compliance requirements for IL5 environments.

This Hybrid position requires that you live within commuting distance from North Charleston, SC.

Responsibilities

This role combines advanced data science, machine learning, AI orchestration, cloud architecture, and software engineering to build scalable, secure, and portable AI solutions capable of supporting mission-critical operations across the PEO Digital portfolio and multiple computing environments.

The ideal candidate is equally comfortable discussing large language models with engineers, presenting AI architecture to senior Government leaders, and leading implementation teams through complex technical challenges.

AI Architecture & Strategy

• Lead the design and implementation of enterprise Agentic AI solutions supporting PEO Digital modernization initiatives.
• Design portable AI architectures capable of operating across Azure, AWS, GCP, and on-premises environments.
• Evaluate technical feasibility of proposed AI capabilities and provide architectural recommendations.
• Develop scalable AI reference architectures that minimize vendor lock-in while maximizing deployment flexibility.
• Recommend emerging AI technologies and best practices supporting future mission requirements.

Agentic AI Development

Lead development of intelligent multi-agent systems including:

• AI orchestration frameworks.
• Autonomous task planning.
• Tool execution.
• Agent collaboration.
• Workflow automation.
• Multi-agent reasoning.
• Retrieval-Augmented Generation (RAG).
• Enterprise knowledge management.

Experience with frameworks such as:

• Semantic Kernel.
• AutoGen.
• LangGraph.
• LangChain.
• CrewAI.
• Similar agent orchestration platforms.

Multi-Cloud & Hybrid Cloud Engineering

Design and support AI deployments utilizing:

• Microsoft Azure
• Azure Arc
• Azure Kubernetes Service (AKS)
• Amazon Web Services (AWS)
• Elastic Kubernetes Service (EKS)
• Google Cloud Platform (GCP)
• Google Kubernetes Engine (GKE)
• Hybrid Cloud architectures
• Edge computing environments
• On-premises Kubernetes deployments
• Develop cloud-agnostic deployment strategies supporting PEO Digital enterprise modernization objectives.

Kubernetes & Container Platforms

Lead containerized AI deployments utilizing:

• Kubernetes.
• Azure Arc-enabled Kubernetes.
• Docker.
• Helm.
• GitOps.
• Infrastructure as Code.
• CI/CD pipelines.

Develop highly portable AI services capable of running in multiple classified and unclassified computing environments.

AI Model Deployment

Design and deploy production AI inference environments utilizing technologies such as:

• Hugging Face.
• vLLM.
• Text Generation Inference (TGI).
• Open-weight Large Language Models.
• Commercial AI services where authorized.

Optimize model performance, scalability, latency, and infrastructure utilization.

Data Science & Machine Learning

Develop advanced analytics and machine learning solutions including:

• Predictive analytics.
• NLP.
• Document intelligence.
• Semantic search.
• Embedding generation.
• Knowledge graph integration.
• AI-assisted decision support.
• Statistical modeling.
• Data mining.
• Feature engineering.

Retrieval-Augmented Generation (RAG)

Design enterprise RAG architectures utilizing:

• Vector databases.
• pgvector.
• Milvus.
• Azure Arc-enabled PostgreSQL.
• Enterprise document repositories.
• Knowledge management systems.

Develop secure document interrogation capabilities supporting mission users.

Security & Compliance

Design AI systems meeting DoD security requirements including:

• Zero Trust Architecture.
• Microsoft Entra ID.
• Identity federation.
• Policy enforcement.
• Controlled Unclassified Information (CUI).
• IL5 environments.
• Audit logging.
• Data governance.
• AI governance.

Implement automated safeguards preventing ingestion or exposure of:

• Personally Identifiable Information (PII).
• Protected Health Information (PHI).

Ensure AI outputs comply with applicable security marking and release requirements.

Technical Leadership

• Lead AI technical strategy across multiple PEO Digital programs.
• Mentor junior data scientists, ML engineers, and software developers.
• Serve as technical advisor to Program Managers and Government stakeholders.
• Present architectural recommendations to executive leadership.
• Support proposal development and technical solutioning for new business opportunities.

Qualifications

• Bachelor's degree in computer science, Data Science, Artificial Intelligence, Engineering, Mathematics, or related technical discipline.
• Active Top Secret Clearance.
• 10+ years of professional experience in Data Science, Machine Learning, AI, or Cloud Engineering.
• 5+ years designing enterprise AI or ML solutions.
• Experience deploying AI solutions in cloud or hybrid-cloud environments.
• Experience with Kubernetes and containerized applications.
• Strong experience architecting multi-cloud AI solutions utilizing Azure, AWS, GCP, and Azure Arc.
• Experience building production machine learning pipelines.
• Strong Python programming skills.
• Experience working with REST APIs and microservices.
• Familiarity with Large Language Models and Generative AI.
• Excellent communication and technical presentation skills.

Preferred Qualifications:

• Master's or Ph.D. in AI, Machine Learning, Computer Science, Data Science, Applied Mathematics, or related discipline.
• Experience supporting Program Executive Office (PEO) Digital, NIWC Atlantic, Marine Corps Systems Command, or other Department of Defense digital modernization organizations.
• Experience with Azure Arc.
• Experience with Azure AI Foundry.
• Experience with AWS Bedrock.
• Experience with Google Vertex AI.
• Experience deploying open-weight LLMs.
• Experience with Semantic Kernel, AutoGen, LangGraph, or similar orchestration frameworks.
• Experience implementing Retrieval-Augmented Generation (RAG).
• Experience with vector databases.
• Experience supporting Department of Defense customers.
• Experience supporting IL5 or classified computing environments.
• Active Secret Clearance or higher.

Preferred Certifications:

• Microsoft Certified: Azure AI Engineer Associate.
• Microsoft Certified: Azure Solutions Architect Expert.
• AWS Certified Machine Learning 6 Specialty.
• Google Professional Machine Learning Engineer.
• Certified Kubernetes Administrator (CKA).
• Certified Kubernetes Application Developer (CKAD).
• Security+.
• PMP (preferred).

Job ID2026-24504 Work TypeHybrid