AI Process Integration Engineer

Geo Owl; Virginia (MN); On-site; USD 110,000 - 140,000; Full time

Job summary

Geo Owl, located in Virginia, MN, is seeking a qualified AI Process Integration Engineer responsible for enhancing AI deployment in intelligence analysis and mission workflows.

The ideal candidate should have over 10 years of experience in AI/ML tool deployment, outstanding analytical skills, and an ability to communicate complex ideas clearly. The position requires a Bachelor's degree in a relevant field and an active TS/SCI clearance.

Qualifications

• 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.
• Active TS/SCI with CI Polygraph required.

Responsibilities

• Evaluate and configure AI tools for operational readiness.
• Map existing workflows to identify bottlenecks and optimize processes.
• Build mission-specific prompt libraries and templates for AI tools.
• Establish KPIs to measure tool utilization and productivity gains.
• Collaborate with stakeholders for smooth adoption of AI workflows.

Skills

AI/ML tool configuration

Prompt engineering

Workflow modeling (BPMN)

Data pipeline management

Analytical thinking

Communication skills

Education

Bachelor's degree in Computer Science, Information Systems, Engineering, or related field

Tools

IC-approved analytic platforms

Job description

Position Description

AI Process Integration Engineer

Job Type: Full-Time

Job Summary

The AI Process Integration Engineer sits 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 Evaluation & 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.

Required Qualifications

• Education: Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
• Experience: 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.
• Technical Skills: 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.
• Methodologies: Working knowledge of Lean Six Sigma, Agile, and continuous improvement frameworks applied to operational or intelligence environments.
• Soft Skills: Strong analytical thinking, clear written and verbal communication, and the ability to translate technical AI capability into practical mission value for non‑technical analysts.
• Clearance: Active TS/SCI with CI Polygraph required.