OverviewWe 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
