Director, Applied AI (Hands-On Technical)

In the Homeland Sector our work helps protect communities and keep critical systems running safely. AI can make a big differencehelping teams detect threats faster make better decisions and build more reliable systemsbut only if it works in real-world operations at scale.

This includes challenges like modernizing air traffic improving airport screening and securing energy infrastructure across the U.S. UK and Australia.

This role offers a rare opportunity to take AI from concept to mission-scale impact across an entire sectorwith access to real mission data production systems and the support needed to deploy at scale.

Must be able to work from the Leidos Reston GHQ. Flexibility with remote with the ability to travel to the corporate office as needed.

As a Hands-On AI Technical Director you will shape how AI is used across the sector. Youll connect new technologies to real mission needs and help teams move from prototypes to production systems that are used every day. Youll stay involved in technical decisions and solution design while helping teams adopt and scale what works.

What Youll Achieve in 612 Months
Deliver at least one production AI capability (not just a prototype) used in a mission workflow
Establish a repeatable path from prototype production scale used by multiple teams
Stand up lightweight MLOps practices (versioning monitoring release) that teams actually use
Launch 23 high-impact pilots with clear decisions to scale or stop

Primary Responsibilities:
Drive AI solutions end-to-endprototype production scalewhile staying involved in design and implementation
Define and lead AI strategy and execution across the Homeland Sector
Provide hands-on technical leadership (prototyping code reviews reference implementations) and guide integration into systemsEstablish practical standards for MLOps governance and responsible AI and apply them in delivery
Evaluate new technologies and run pilots with clear criteria for scaling or stopping
Partner with teams and customers to deliver high-impact AI solutions
Share and scale what works across programs (reuse and standard approaches)

Basic Qualifications:
Masters degree and 15 years experience in a related field with or equivalent practical experience building and scaling AI systems. Additional years experience may be used in lieu of degree.
Experience leading development and production deployment of AI/ML solutions
Strong grounding in ML data systems and model lifecycle management with hands-on experience in modern frameworks and cloud platforms
Experience integrating AI into real operational systems
Proven ability to lead across teams while staying close to the work with strong communication skills
Eligible to obtain and maintain a U.S. security clearance (U.S. citizenship required; we support the process)

Preferred Qualifications:
Experience in mission-critical or regulated environments (e.g. defense healthcare finance)
Experience with generative AI / LLMs and applying them in real-world systems
Experience scaling AI across organizations or portfolios (driving adoption standardization and reuse)Experience operating AI in production (MLOps model governance monitoring reliability)
Experience building cloud-native AI platforms (containerization Kubernetes modern data platforms)
Active security clearance
Track record of technical leadership or influence (e.g. leading initiatives mentoring open source publications)

If youre looking for comfort keep scrolling. At Leidos we outthink outbuild and outpace the status quo because the mission demands it. Were not hiring followers. Were recruiting the ones who disrupt provoke and refuse to fail. Step 10 is ancient history. Were already at step 30 and moving faster than anyone else dares.

Original Posting:

Pay Range:

The Leidos pay range for this job level is a general guideline onlyand not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job education experience knowledge skills and abilities as well as internal equity alignment with market data applicable bargaining agreement (if any) or other law.