Vice President of Technology AI and ML
PMAT, Inc. · United States · 2026-10-08
About this role
At PMAT, we work on mission critical systems that directly support the warfighter, designing, building, and securing modern digital capabilities across cloud, data, and software environments. Our teams tackle complex, real-world challenges where delivery matters more than theory, and innovation is driven by curiosity, collaboration, and purpose.
In this role, you’ll contribute to enterprise data, artificial intelligence (AI), machine learning (ML), and advanced technology capabilities, working alongside engineers and operators to deliver resilient, forward-leaning solutions in support of national defense.
About the role: PMAT is seeking a technically accomplished and commercially oriented Vice President of Technology AI and ML to lead the company’s enterprise-wide data, AI, and ML strategy. Reporting directly to the Chief Operations Officer (COO), the VP of Technology will serve as PMAT’s senior executive responsible for transforming data and AI capabilities into strategic business assets. You’ll establish scalable data and AI architectures, integrate AI/ML into PMAT’s products, platforms, and operations, and help translate emerging technologies into practical, mission-focused capabilities for Department of Defense (DoD), Intelligence Community (IC), and other federal customers. Working across executive leadership, Growth, Engineering, Program Management, SBIR, and Advanced Technology, you’ll help identify new market opportunities, develop differentiated technical capabilities, transition innovations from research and prototyping into operational deployments, and connect technology investments to measurable business and mission outcomes.
Responsibilities:
• Develop and execute PMAT’s enterprise-wide data, AI, and ML strategy, including a long-term technology roadmap encompassing generative and agentic AI, predictive analytics, computer vision, natural language processing, intelligent automation, and emerging technologies. Advise the COO and executive leadership on technology trends, market opportunities, investment priorities, and the strategic implications of AI and data-driven capabilities.
• Lead the design and implementation of scalable, secure, and modular AI/ML architectures and establish technical standards for data ingestion and integration, model development, deployment, orchestration, monitoring, and lifecycle management. Direct solutions involving large language models (LLMs), retrieval-augmented generation (RAG), autonomous and agentic systems, predictive analytics, advanced decision support, MLOps, LLMOps, and DataOps.
• Guide development of cloud-native, hybrid-cloud, edge, disconnected, classified, and tactical AI architectures; evaluate and integrate commercial, open-source, and government-developed technologies; oversee prototyping and proof-of-concept development; and ensure architectural alignment across PMAT’s technology portfolio, including Overmatch and Tactical Edge Node capabilities.
• Establish PMAT’s enterprise data strategy, including data architecture, governance, quality, integration, security, interoperability, and lifecycle management. Lead development of scalable data infrastructure, pipelines, data lakes/lakehouses, streaming architectures, and enterprise data platforms while establishing governance standards for ownership, classification, access, lineage, quality, retention, and interoperability.
• Partner with the COO, Chief Growth Officer, and executive leadership to develop growth strategies leveraging PMAT’s AI/ML, data, and advanced analytics capabilities. Identify and support federal business opportunities, develop differentiated technical solutions and value propositions, participate in customer engagements and strategic partnerships, and support captures and proposals through technical strategy, solution architecture, innovation roadmaps, and differentiated AI/ML approaches.
• Partner with PMAT’s SBIR and Advanced Technology teams to translate customer mission requirements into technical architectures, development roadmaps, prototypes, demonstrations, and operational solutions. Leverage SBIR/STTR and other technology-development programs to mature innovative capabilities, develop reusable AI/ML components, frameworks, models, platforms, and intellectual property, and transition successful innovations into operational capabilities, Phase III opportunities, and production programs.
• Establish and oversee PMAT’s enterprise AI governance framework, ensuring AI/ML solutions align with applicable federal requirements, relevant NIST AI Risk Management Framework principles, cybersecurity standards, and agency-specific requirements. Integrate security, privacy, explainability, model validation, human oversight, and risk management into AI/ML development and address model vulnerabilities, data poisoning, adversarial threats, model drift, and third-party technology risk.
• Build and lead high-performing teams across data science, AI/ML engineering, data engineering, AI architecture, and advanced analytics. Establish organizational structure, talent strategy, development standards, operating budgets, investment priorities, and performance measures while driving technical excellence, innovation, accountability, knowledge sharing, operational efficiency, and scalable delivery across programs and customers. Establish and achieve measurable outcomes across AI/ML strategy execution; revenue growth and qualified pipeline; capture participation and contract awards; product and technology development; enterprise AI/ML adoption; operational efficiency; technical performance and scalability; talent acquisition, retention, and development; financial performance and return on technology investments; AI governance and security; strategic customer engagement; SBIR/STTR support; Advanced Technology collaboration; and the transition of AI/ML innovations into funded initiatives, Phase III awards, operational deployments, and production programs.
About Us: PMAT is…
Skills asked for
- machine learning
- computer vision
- cybersecurity
- data science
- aws
- azure
- google cloud
- databricks
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