Job Description Summary

The Senior Director, AI Enablement will build and lead a new, Defense & Systems Digital Technology function focused on accelerating value realization from AI. This leader will partner closely with business stakeholders and customers to translate prioritized opportunities into actionable plans, and orchestrate end-to-end delivery—from problem framing and data enablement through development, deployment, and value tracking. The role requires a seasoned leader who can stand up a high-performing team, scale operating mechanisms, create standards, and coordinate execution across teams including Business P&Ls, Data Science, AI Factory, and Infrastructure teams.

Job Description

Key Responsibilities:

Strategy and Vision

• Define and socialize a clear strategy to accelerate value from AI/analytics across priority business domains and customer programs
• Establish an intake framework to prioritize use cases based on impact and make the demand easily visible 
• Create KPIs that measure value realization, adoption, scalability, and operational reliability

Team Building and Leadership

• Build a new team from the ground up, including hiring, onboarding, coaching, and workforce planning
• Stand up core capabilities: Program Management,  Data Architecture/Engineering, Application / Cloud Engineering, Ops, etc. 
• Foster a culture of safety, quality, continuous improvement, and customer focus

Business and Customer Partnership

• Serve as a trusted partner to business leaders and customers to understand outcomes, constraints, and readiness
• Develop problem statements, success criteria, and value hypotheses; align on ROI, timelines, and governance
• Communicate progress through executive-ready artifacts and regular operating rhythms

End-to-End Delivery and Orchestration

• Lead cross-functional execution spanning AI Enablement, Business Teams,  Data Science, AI Factory, and Infrastructure
• Ensure robust designs and model for lifecycle management, scalable deployment patterns, and proper handoffs to run-state are created and implemented 

Governance, Risk, and Compliance

• Implement data governance, privacy, security, and responsible AI practices aligned to company strategy and in compliance with applicable regulations. 
• Establish Model Risk Management processes, including documentation, testing, monitoring, and periodic reviews
• Define and enforce standards for data quality, lineage, observability, and resilience

Operating Mechanisms and Continuous Improvement

• Implement standard work for discovery, experimentation, pilot, scale, and run-state phases
• Create feedback loops with business units to improve speed, quality, and adoption
• Drive post-implementation reviews to verify value realization 
• Inform AI educational and skill development strategy across Defense and Systems Digital Technology 

Minimum Qualifications:

• Bachelor’s degree from accredited university or college with minimum of 10 years of professional experience OR Associates degree with minimum of 13 years of professional experience OR High School Diploma with minimum of 15 years of professional experience
• Minimum 7+ years of experience in Data/Analytics/AI, with 6+ years leading multi-disciplinary teams and complex portfolios
• Note: Military experience is equivalent to professional experience
• Eligibility Requirement:
• Legal authorization to work in the U.S. is required.  We will not sponsor individuals for employment visas, now or in the future, for this job.

Preferred Experience

• Demonstrated success building new teams/functions and scaling operating mechanisms
• Proven track record delivering measurable business outcomes with AI/ML, analytics platforms, and data products
• Strong grasp of data concepts; ETL/ELT, lake/lakehouse, Data Fabric, analytics, Ontologies, and AI/MLOps/ModelOps/AI 
• Experience coordinating across teams Data Science, infrastructure, cybersecurity, and enterprise architecture
• Executive presence with excellent communication, stakeholder management, and change leadership skills
• Familiarity with responsible AI, data governance, and model risk management
• Standing up and or management of a professional service function 
• Leading AI/ML delivery in regulated or safety-critical environments
• Building product-oriented delivery (backlogs, roadmaps, OKRs) and value tracking frameworks
• Work