Lead Artificial Intelligence (AI) Engineer

Type of Requisition: Pipeline Clearance Level Must Currently Possess: Top Secret SCI + Polygraph Clearance Level Must Be Able to Obtain: Top Secret SCI + Polygraph Public Trust/Other Required: None Job Family: Data Science and Data Engineering Job Qualifications: Skills: AI Concepts, AI Systems, Artificial Intelligence (AI), Data Science, Machine Learning (ML) Certifications: None Experience: 5 + years of related experience US Citizenship Required: Yes Job Description: Why GDIT Are you ready to be a part of an elite team at GDIT, working on a large-scale, pioneering National Intelligence program? This is an incredible opportunity to immerse yourself into an environment that fuses innovation, speed, and security to safeguard our Nation. At GDIT, you'll thrive in a dynamic and collaborative setting, where your technical skills will be both challenged and expanded. This program offers the chance to engage with cutting-edge technologies and contemporary development practices in support of a vital mission. You'll play a critical role in addressing some of the most intricate security and operational challenges facing Intelligence and Homeland Security today. Come join us and contribute to a mission that truly matters, while advancing your career alongside some of the brightest minds in the industry. What You’ll Achieve • The Lead AI Engineer will serve as the innovation and technical AI lead across a six–Task Order (TO) software-development IDIQ portfolio. Operating within the Program Management Office (PMO) and reporting directly to the Solution Architect, this role is responsible for: • • Rationalizing and optimizing the solution portfolio • Guiding AI/ML and automation insertion across multiple TOs • Driving continuous improvement in delivery processes and technical solutions • Leading selection of AI models based on use case and performance requirements, including model optimization and tuning • Exploring use of open-weight/open-source models to reduce token consumption across the program and TOs • Collaborating with customer on adoption of new and emerging AI capabilities • Ensuring cost, schedule, and performance objectives are met across completion-based task orders • The ideal candidate combines deep AI/ML engineering expertise with strong systems-thinking, software delivery experience, and the ability to influence stakeholders across a complex program environment. Key Responsibilities • Portfolio-Level AI Leadership • • Develop and maintain an AI/ML strategy for the six–Task Order IDIQ portfolio, aligned with enterprise architecture and program objectives. • Assess current systems and capabilities to identify opportunities for AI-driven enhancements, cost savings, and performance improvements. • Rationalize overlapping solutions and tools across task orders, driving reuse, common services, and standardized approaches to AI/ML. • AI Insertion & Technical Execution • • Architect and guide the design, development, integration, and deployment of AI/ML solutions (e.g., predictive analytics, NLP, recommendation engines, intelligent automation) into existing and new applications. • Leverage GDIT enterprise accelerators—including ALAMO, Coral, and SDAF—to rapidly design, prototype, and operationalize AI capabilities across the portfolio. • Coordinate with corporate reach-back and centralized GDIT accelerator teams to ensure effective adoption, configuration, and continuous enhancement of ALAMO, Coral, and SDAF within program solutions. • Partner with individual TO technical leads to define use cases, data requirements, model selection, training pipelines, and MLOps practices. • Establish and enforce best practices for AI model lifecycle: experimentation, evaluation, deployment, monitoring, retraining, and retirement. • Ensure AI solutions are secure, auditable, explainable, and compliant with applicable regulations and customer policies • Continuous Improvement & Innovation • • Drive continuous improvement across the portfolio by introducing modern engineering practices (MLOps, DevSecOps, CI/CD, infrastructure as code, automated testing, observability). • Lead proof-of-concept and rapid prototyping efforts to validate new AI capabilities before scaling. • Track industry trends and emerging AI technologies, and evaluate their applicability to the program. • Define metrics and KPIs to measure the impact of AI initiatives on mission outcomes, user experience, and operational efficiency. • Legacy Transition & Modernization • • Lead technical planning and execution for transitioning legacy systems and workflows to modern architectures, including cloud-native and AI-enabled platforms. • Perform technical and architectural assessments of legacy applications and data sources to inform migration and modernization strategies. • Collaborate with PMO and TO leadership to sequence and manage transitions to minimize risk and disruption to operations. • Cost, Schedule, and Performance Management • • Support PMO and Solution Architect in estimating AI-related work, defining scope, and planning for cost-effective delivery. • Identify and mitigate technical risks impacting schedule and performance across completion-based task orders. • Provide regular status updates, technical roadmaps, and decision support to PMO leadership and customer stakeholders. • Ensure AI initiatives are aligned with contractual requirements, performance objectives, and quality standards. • Collaboration & Stakeholder Engagement • • Work closely with TO leads, software engineers, data engineers, business analysts, and UX teams to integrate AI into end-to-end solutions. • Engage customer stakeholders to refine requirements, demonstrate AI capabilities, and support change management and adoption. • Mentor and guide engineering teams on AI/ML concepts, tools, and best practices, building a strong internal AI capability. Required Qualifications • Bachelor’s degree in Computer Science, Engineering, Math