Senior Data Scientist – Agentic AI & Multi-Cloud Architecture - Active Top Secret Clearance

We are seeking an experienced Senior 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 person will be a practical visionary and will be someone who can help PEO Digital not only leverage AI today but literally help chart its path forward with AI for the entire Naval ecosystem: identifying where it can transform the mission, determining the right technologies and architectures, and then helping us actually build and deploy those capabilities.

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

This position offers the opportunity to shape the future of Artificial Intelligence across the PEO Digital portfolio by architecting enterprise-scale Agentic AI capabilities that support secure, multi-cloud operations across Azure, AWS, Google Cloud Platform, and on-premises environments. You will work alongside Government leaders, cloud architects, software engineers, cybersecurity professionals, and mission partners to deliver innovative AI solutions that accelerate digital modernization, improve mission effectiveness, and enable next-generation decision support for the Department of the Navy. To join our team of outstanding professionals, apply today!

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