Overview

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 is a remote position that may require significant travel, up to or more than 25% of the time.

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.

Desired 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.
• Desired 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).

This position is contingent upon contract award and funding. Applicants selected may be offered but cannot begin work until funding has been confirmed.

Benefits InformationRegular - The company offers a comprehensive benefits program, including medical, dental, vision, life insurance, 401(k) and a range of other voluntary benefits. Paid Time Off (PTO) is offered to regular full-time and part-time employees. Pay Range$160,000 - $220,000 Job ID2026-25171 Work TypeRemote