AI Process Integration Engineer

Quick Services•Sterling, VA

1d•Onsite

About The Position

This role focuses on integrating Artificial Intelligence (AI) and Machine Learning (ML) tools into existing analytic and targeting workflows within the customer's network. The engineer will be responsible for evaluating AI tools, configuring them for operational readiness, optimizing their use, and redesigning workflows to leverage AI capabilities. This includes developing mission-specific use cases, creating prompt libraries, and ensuring seamless integration with minimal disruption to analysts. The position also involves establishing performance metrics, collaborating with stakeholders, and driving the adoption of AI-enabled processes. A key aspect is acting as a liaison between technical teams, the analytic workforce, and leadership to translate AI capabilities into practical mission value.

Requirements

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.
Proficiency in prompt engineering.
Proficiency in workflow modeling (BPMN).
Proficiency in data pipeline management.
Experience with IC-approved analytic platforms.
Experience with multi-classification network environments.
Working knowledge of Lean Six Sigma.
Working knowledge of Agile.
Working knowledge of continuous improvement frameworks applied to operational or intelligence environments.
Strong analytical thinking.
Clear written and verbal communication.
Ability to translate technical AI capability into practical mission value for non-technical analysts.
Active TS/SCI with CI Polygraph required.

Responsibilities

Assess approved AI/ML tools for operational readiness, configuration gaps, and underutilization.
Configure, optimize, and integrate approved tools into existing analytic and targeting workflows.
Develop mission-specific use-case configurations for tasks such as entity triage, credibility scoring, pattern correlation, document production, and RFI processing.
Maintain tool performance baselines and identify adjustments to improve output accuracy, speed, and analyst adoption.
Map current-state workflows to identify AI integration opportunities for eliminating manual bottlenecks, reducing redundant data entry, and compressing cycle times.
Design optimized future-state workflows embedding AI tool touchpoints.
Develop before/after process documentation with measurable performance targets.
Maintain SOPs and workflow guides for integrated AI-enabled processes.
Build mission-specific prompt libraries, Boolean-to-AI logic translation guides, and structured templates.
Develop a Document Support Playbook Suite covering draft assist, tradecraft review, source synthesis, consistency checking, and classification review.
Ensure prompt engineering products are tool-agnostic and adaptable.
Establish KPIs to track AI tool utilization, analyst productivity, cycle time reductions, and product quality improvements.
Provide data-driven evidence to leadership supporting decisions on AI tool access and use cases.
Apply Lean Six Sigma and continuous improvement methodologies to refine AI-integrated workflows.
Work directly with analysts, targeters, mission leads, and IT teams to drive adoption of AI-integrated workflows.
Develop transition plans and training materials for smooth integration of AI tools.
Serve as the operational bridge between technical AI/ML engineering, the analytic workforce, and program leadership.