Enterprise Capabilities Architect – Digital Transformation, AI, and Data Architect

Responsibilities

Peraton is looking for a Digital Transformation, AI, and Data Architect to join the Corporate Growth, Enterprise Capabilities and Solutions team as one of the technical leads behind our most competitive pursuits. You will provide thought leadership and design differentiated service offerings, architectures, and technical strategies for digital modernization, artificial intelligence, and data-driven mission outcomes. These provide the people and process elements to the Peraton Labs technology developments. You will work directly alongside capture teams, growth leaders, sector CTOs, and technical SMEs from early strategic opportunity shaping through proposal submission to build solutions that win contracts and frameworks that make winning repeatable. If you are energized by high-stakes technical challenges and want to see your work translate directly into contract wins, this role was built for you.

What you’ll do:

• Lead the Peraton Enterprise Capabilities and Solutions Portfolio for Digital Modernization, Artificial Intelligence, and Data from strategy through execution, ensuring every offering is aligned to business priorities, technically sound, and built to compete across all Peraton customer’s market spaces.
• Work directly with capture teams, sector growth leaders, and SMEs to shape Digital Transformation and AI/Data solutions from early opportunity identification through proposal submission.
• Develop technical discriminators, solution narratives, and competitive positioning materials that support capture and proposal efforts across the enterprise, with deep credibility in digital modernization, AI/ML architecture, and data platform design.
• Design and develop scalable, reusable digital transformation and AI/Data service offerings, architectures, and technical frameworks that give Peraton's sector teams a competitive edge on federal pursuits.
• Continuously evolve the portfolio by analyzing capability gaps, technology readiness, and market trends across federal digital modernization and AI adoption to identify portfolio enhancements and competitive differentiation opportunities that strengthen Peraton's position in core markets.
• Provide thought leadership and author white papers and other solution artifacts to support customer engagement efforts highlighting newly developed frameworks and Peraton Labs applicable technologies.
• Partner with sector growth teams, business stakeholders, and engineering leadership to translate market opportunities into viable, differentiated service offerings.
• Drive the design and architecture of services across the portfolio. Ensure each service is fully defined with supporting sales assets, cost models, and solution guides that equip sector teams to sell and deliver.
• Present technical strategies, AI/Data architecture roadmaps, and digital modernization solution recommendations to customers, capture teams, and executive leadership with the clarity and confidence to drive decisions.
• Engage with key customers, industry partners, and technology vendors to stay ahead of evolving federal AI policy, emerging data platform capabilities, and competitive dynamics in Peraton's target markets.

Qualifications

Required Qualifications:

• Bachelor’s degree in computer science, data science, data management, information technology, systems engineering, or related field, and 16+ years of industry experience OR 14+ years with a Master’s OR 10+ years with a PhD
• Deep expertise in AI/ML platform architecture including model development, training, and deployment pipelines, with demonstrated experience integrating AI and generative AI capabilities into enterprise or mission applications
• Proven experience designing and implementing modern data platform architectures including data lakes, data mesh, and data fabric, with strong command of data governance, data quality, and data management frameworks in a federal environment
• Demonstrated experience with MLOps practices and AI lifecycle management, from development and testing through production deployment and continuous monitoring
• Demonstrated experience with Data Management Body of Knowledge (DMBoK), Data Management Capability Assessment Models (DCAM), Findable, Accessible, Interoperable, and Reusable (FAIR) Data Principles, and/or Control Objectives for Information and Related Technologies (COBIT)
• Working knowledge of legacy system modernization strategies, application migration approaches, and API-first and microservices-based architecture patterns that accelerate digital transformation
• Demonstrated experience applying human-centered design principles and iterative user research methods to federal digital transformation programs, with measurable outcomes in user adoption and missio