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Supporting critical missions at the intersection of data and science, KeyLogic provides mission management, systems analysis, data analytics, digital transformation, and cybersecurity to customers in the energy, federal civilian, and defense sectors, with a 20+ year portfolio of successes supporting DOE, DOC, EPA, DOD, DHS, FBI, and other federal agencies challenged with complex missions. We help our customers solve the world’s most challenging problems with unsurpassed anticipatory service.
KeyLogic employs over 400 team members, including systems designers, developers, data scientists, IT and cybersecurity specialists, engineers, mission experts, program managers, and more than 70 Ph.D. scientists. This multidisciplinary team works together solving challenging problems with anticipatory service—always staying one step ahead—benefiting our customers, and ultimately helping build a better world.
We are committed to the success of each customer’s mission. We care enough to make their mission our mission and their success our success. We take technical service delivery to a level above our peers. Our anticipatory service is best-in-class.
Senior Artificial Intelligence Advisor
KeyLogic
On-site
Hybrid Morgantown, WV, United States
Full-time
$80,000 -
$200,000
About KeyLogic
About the Role
KeyLogic is seeking an experienced Senior Artificial Intelligence Advisor to guide artificial intelligence initiatives in support of the U.S. Department of Energy (DOE). This role will shape how AI enhances scientific discovery, accelerates R&D, modernizes operations, and strengthens mission impact across the complex. The ideal candidate combines deep expertise in AI/ML with consulting agility, business development skills, and the ability to envision "art of the possible" applications across scientific domains, advanced energy systems, digital engineering, and laboratory operations. This position balances strategy, execution, technical leadership, and the development of new opportunities that mature into funded programs.
Qualifications
U.S. Citizenship.
Bachelor's degree required; Master's or PhD. in Computer/Data Science, Engineering/Applied Math, and/or Scientific Modeling preferred with demonstrated capabilities required in Physical/Fundamental Science.
5-10+ years' experience in AI/ML, scientific computing, digital transformation, or advanced analytics.
5- 10+ years leading AI/ML projects with executive or senior stakeholder engagement.
Demonstrated ability to build partnerships and develop new business opportunities within federal R&D, government, or scientific institutions.
Experience supporting DOE, National Laboratories, ARPA-E, DoW, or NSF research programs.
Prior work in scientific ML, HPC-AI Integration, digital twins, physics-informed modeling, or computational science.
Knowledge of AI governance, responsible AI frameworks, and federal compliance standards.
Experience developing proposals, capture strategies, and R&D concepts.
Understanding of DOE energy systems, materials science, climate/energy analysis, or advanced engineering domains.
AI certifications or cloud certifications (e.g. NVIDIA, AWS, Azure, Databricks).
Exposure to agile program management and design-thinking methodologies.
Ability to synthesize technical depth with strategic vision.
Proven success leading teams and managing large, complex programs.
Strong interpersonal and communication skills to influence stakeholders at all levels.
Comfort operating in mission-driven, highly technical, and ambiguous environments.
Entrepreneurial mindset with a bias toward action and building new capabilities.
Bachelor's degree required; Master's or PhD. in Computer/Data Science, Engineering/Applied Math, and/or Scientific Modeling preferred with demonstrated capabilities required in Physical/Fundamental Science.
5-10+ years' experience in AI/ML, scientific computing, digital transformation, or advanced analytics.
5- 10+ years leading AI/ML projects with executive or senior stakeholder engagement.
Demonstrated ability to build partnerships and develop new business opportunities within federal R&D, government, or scientific institutions.
Experience supporting DOE, National Laboratories, ARPA-E, DoW, or NSF research programs.
Prior work in scientific ML, HPC-AI Integration, digital twins, physics-informed modeling, or computational science.
Knowledge of AI governance, responsible AI frameworks, and federal compliance standards.
Experience developing proposals, capture strategies, and R&D concepts.
Understanding of DOE energy systems, materials science, climate/energy analysis, or advanced engineering domains.
AI certifications or cloud certifications (e.g. NVIDIA, AWS, Azure, Databricks).
Exposure to agile program management and design-thinking methodologies.
Ability to synthesize technical depth with strategic vision.
Proven success leading teams and managing large, complex programs.
Strong interpersonal and communication skills to influence stakeholders at all levels.
Comfort operating in mission-driven, highly technical, and ambiguous environments.
Entrepreneurial mindset with a bias toward action and building new capabilities.
Responsibilities
Advance AI Strategy and Vision:
Develop and drive an AI strategy aligned with DOE mission priorities, scientific roadmaps, and future state operating models.
Identify high-value AI applications across research, modeling, simulation, energy systems, materials discovery, cyber, facility operations, and mission support.
Translate emerging AI technologies (e.g. LLMs, multimodal models, agentic AI, scientific ML, HPC-AI fusion) into actionable pathways that maximize value for the Lab.
Shape and Deliver High-Impact AI Initiatives:
Lead multidisciplinary teams in designing and implementing AI solutions that improve insight generation, scientific productivity, model accuracy, operational efficiency, and decision support.
Integrate AI into existing Lab tools, platforms, and workflows to modernize and scale capabilities.
Guide technical design, architecture, and research direction for pilots, prototypes, and full-scale solutions.
Business Development and Opportunity Advancement:
Identify, shape, and mature AI-driven opportunities with DOE programs, other national laboratories, academia, and industry partners.
Lead the development of concepts, white papers, proposals, and partnership strategies.
Drive prioritization of AI investments based on Value, feasibility, mission impact, and risk.
Serve as a primary interface with DOE sponsors, advocating for the Lab's AI capabilities and securing new funding.
Operationalize Responsible, Scalable AI:
Establish governance, model risk management, data practices, and responsible AI frameworks tailored to DOE R&D.
Support ModelOps/MLOps implementation, ensuring transparency, reproducibility, and long-term sustainability.
Champion ethical, secure, and compliant adoption of AI across scientific and operational environments.
Team Leadership & Workforce Development:
Build and lead high-performing teams of AI scientists, engineers, domain experts, and analysts.
Mentor staff and grow a scalable internal AI capability that can support diverse mission needs.
Coordinate with technical and operational leaders to align talent, resources, and execution plans.
Stakeholder Engagement & Thought Leadership:
Represent the Lab in high-level discussions with DOE leadership, inter-laboratory AI working groups, academia, and industry collaborators.
Communicate complex AI topics to technical and non-technical audiences.
Serve as a thought-leader in emerging AI technologies relevant to scientific R&D, energy systems, digital twins, and operational excellence.
Develop and drive an AI strategy aligned with DOE mission priorities, scientific roadmaps, and future state operating models.
Identify high-value AI applications across research, modeling, simulation, energy systems, materials discovery, cyber, facility operations, and mission support.
Translate emerging AI technologies (e.g. LLMs, multimodal models, agentic AI, scientific ML, HPC-AI fusion) into actionable pathways that maximize value for the Lab.
Shape and Deliver High-Impact AI Initiatives:
Lead multidisciplinary teams in designing and implementing AI solutions that improve insight generation, scientific productivity, model accuracy, operational efficiency, and decision support.
Integrate AI into existing Lab tools, platforms, and workflows to modernize and scale capabilities.
Guide technical design, architecture, and research direction for pilots, prototypes, and full-scale solutions.
Business Development and Opportunity Advancement:
Identify, shape, and mature AI-driven opportunities with DOE programs, other national laboratories, academia, and industry partners.
Lead the development of concepts, white papers, proposals, and partnership strategies.
Drive prioritization of AI investments based on Value, feasibility, mission impact, and risk.
Serve as a primary interface with DOE sponsors, advocating for the Lab's AI capabilities and securing new funding.
Operationalize Responsible, Scalable AI:
Establish governance, model risk management, data practices, and responsible AI frameworks tailored to DOE R&D.
Support ModelOps/MLOps implementation, ensuring transparency, reproducibility, and long-term sustainability.
Champion ethical, secure, and compliant adoption of AI across scientific and operational environments.
Team Leadership & Workforce Development:
Build and lead high-performing teams of AI scientists, engineers, domain experts, and analysts.
Mentor staff and grow a scalable internal AI capability that can support diverse mission needs.
Coordinate with technical and operational leaders to align talent, resources, and execution plans.
Stakeholder Engagement & Thought Leadership:
Represent the Lab in high-level discussions with DOE leadership, inter-laboratory AI working groups, academia, and industry collaborators.
Communicate complex AI topics to technical and non-technical audiences.
Serve as a thought-leader in emerging AI technologies relevant to scientific R&D, energy systems, digital twins, and operational excellence.
