A.I. Process Integration Engineer - SME - TS & CI Poly required to apply - NCR in Reston

Energy Jobline ZR; Reston (VA); On-site; USD 130,000 - 170,000; Full time

Job summary

Energy Jobline ZR seeks an AI Process Integration Engineer to bridge AI tool deployment with mission workflows across intelligence analysis and targeting. You will redesign processes around existing tools, configure them for mission use, and ensure analysts can use them from Day 1.

The role demands 10+ years in AI/ML tool deployment and 5+ years with IC/DoD environments, plus Lean Six Sigma and prompt engineering expertise. A TS/SCI with CI Polygraph clearance is required.

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
• 10+ years of AI/ML tool deployment, systems integration, or business process engineering; 5+ years in IC/DoD/federal analytic environments.
• Proficiency in AI/ML tool configuration, prompt engineering, workflow modeling, and data pipeline management.

Responsibilities

• Evaluate and configure approved AI/ML tools for operational readiness and integration into analytic workflows.
• Map current workflows and design optimized future-state processes embedding AI touchpoints.
• Develop mission-specific prompt libraries and templates enabling tool usability for analysts.

Skills

AI tool deployment

Systems integration

Lean Six Sigma

Process modeling

Prompt engineering

Education

Bachelor's degree in CS/IS/Engineering

Tools

BPMN

Data pipelines

AI/ML platforms

Job 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 & ConfigurationAssess 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 RedesignMap 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 EnablementBuild 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 ImprovementEstablish 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 ManagementWork 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

Required QualificationsEducation: 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.