Intelligence Analytics AI/ML Instructor

Leidos LLC; Hampton (VA); On-site; USD 66,000 - 119,000; Full time

Benefits offered by this job

Competitive compensation

Health and Wellness programs

Job summary

Leidos is seeking an Intelligence Analytics Instructor at Joint Base Langley–Eustis in Hampton, VA to deliver classroom and virtual instruction on AI/ML concepts, LLMs, RPA, and data analytics to Air Force intelligence professionals.

The role requires tailoring training to varying proficiency levels, providing hands-on support across domains from Unclassified to AFSCI, and translating traditional workflows into AI/ML-augmented processes.

Qualifications

• Familiarity with basic data analytics, LLMs, and AI/ML related concepts.
• Understanding of intelligence processes and organizational responsibilities within the AF and the Intelligence Community.
• Effective written and oral communication skills, including ability to communicate detailed technical information to peers and non-technical management staff as needed
• Knowledge of Microsoft Office

Responsibilities

• Deliver formal classroom and virtual instruction on tool-agnostic AI/ML concepts, LLMs, RPA, and advanced data analytics.
• Execute tiered role-based training, adapting delivery to varying student proficiency levels.
• Instruct personnel on AI/ML methodologies to build trust, proficiency, and critical thinking.
• Provide hands-on, over-the-shoulder support across Unclassified, Secret, and AFSCI domains.
• Assist analysts in developing TTPs to modernize intelligence workflows with AI/ML.

Skills

Data analytics

LLMs

AI/ML concepts

Effective communication

Microsoft Office

Job description

Leidos is seeking an Intelligence Analytics Instructor at Joint Base Langley–Eustis in Hampton, VA to deliver classroom and virtual instruction on AI/ML concepts, LLMs, RPA, and data analytics to Air Force intelligence professionals.

The role requires tailoring training to varying proficiency levels, providing hands-on support across domains from Unclassified to AFSCI, and translating traditional workflows into AI/ML-augmented processes.