AI Process Integration Engineer

Peraton is seeking an AI Process Integration Engineer.  This position will sit at the intersection of artificial intelligence deployment and mission workflow optimization — responsible for bridging the gap between approved, available AI/ML tools and their effective operational use across intelligence analysis, targeting, and screening and vetting workflows. This role does not wait for new tools to be approved; it maximizes the mission value of what is already on the network by redesigning the processes around those tools, configuring them for mission-specific use cases, and ensuring analysts can leverage them from Day 1.

Key Responsibilities

AI Tool Deployment & Configuration

• Assess approved AI/ML tools currently available on the customer network and evaluate their operational readiness, configuration gaps, and underutilization.
• Configure, optimize, and integrate approved tools into existing analytic and targeting workflows without introducing unapproved capabilities or triggering additional review board requirements.
• Develop mission-specific use-case configurations that align tool functionality to analyst tasks — entity triage, credibility scoring, pattern correlation, document production, and RFI processing.
• Maintain tool performance baselines and identify configuration adjustments that improve output accuracy, speed, and analyst adoption.

Workflow Analysis & Process Redesign

• Map current-state analytic and operational workflows to identify where approved AI tools can eliminate manual bottlenecks, reduce redundant data entry, and compress cycle times.
• Design optimized future-state workflows that embed AI tool touchpoints at the highest-friction points in the intelligence production and targeting cycle.
• Develop before/after process documentation with measurable performance targets tied directly to mission outcomes.
• Maintain SOPs and workflow guides that reflect the integrated AI-enabled process architecture.

Prompt Engineering & Tool Enablement

• Build mission-specific prompt libraries, Boolean-to-AI logic translation guides, and structured templates that make approved tools immediately usable by analysts without requiring technical expertise.
• Develop a Document Support Playbook Suite covering draft assist, tradecraft review, source synthesis, consistency checking, and classification review workflows.
• Ensure all prompt engineering products are tool-agnostic and adaptable to any customer-approved platform upgrade or replacement.

Performance Measurement & Continuous Improvement

• Establish KPIs tracking AI tool utilization rates, analyst productivity gains, cycle time reductions, and product quality improvements.
• Provide leadership with data-driven evidence supporting review board decisions to expand AI tool access or activate additional use cases.
• Apply Lean Six Sigma and continuous improvement methodologies to iteratively refine AI-integrated workflows based on operational feedback.

Stakeholder Collaboration & Change Management

• Work directly with analysts, targeters, mission leads, and IT teams to drive adoption of AI-integrated workflows through hands-on demonstration, embedded support, and structured enablement.
• Develop transition plans and training materials that ensure smooth integration of AI tools into daily mission operations with zero workflow disruption.
• Serve as the operational bridge between the technical AI/ML engineering team, the analytic workforce, and program leadership.

****This position is contingent on contract award***

Required Qualifications

• Active TS/SCI with Polygraph required
• 12 years of experience, may have supervisory or management experience
• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
• 10+ years of experience in AI/ML tool deployment, systems integration, or business process engineering; at least 5 years supporting IC, DoD, or Federal law enforcement analytic environments.
• Proficiency in AI/ML tool configuration, prompt engineering, workflow modeling (BPMN), and data pipeline management; experience with IC-approved analytic platforms and multi-classification network environments.
• Working knowledge of Lean Six Sigma, Agile, and continuous improvement frameworks applied to operational or intelligence environments.
• Strong analytical thinking, clear written and verbal communication, and the ability to translate technical AI capability into practical mission value for non-technical analysts.