Hiring.Camp

Lead Artificial Intelligence (AI) Engineer

Gdit

·

Today

Salary
$170k – $229k
Location
USA VA Chantilly - Customer Proprietary (VAC034), United States of America
Type
Full-time
Department
Engineering
Seniority
Lead
Experience
5+ years
Education
PhD
Source
Workday

Description

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, Mathematics, Data Science, or related field; or equivalent experience.
  • 5+ years of professional experience in software engineering and/or AI/ML engineering.
  • Proven experience designing, developing, and deploying AI/ML solutions in production environments.
  • Hands-on experience with common AI/ML frameworks and tools (e.g., TensorFlow, PyTorch, scikit-learn, Transformers, spaCy, Hugging Face, etc.).
  • Strong proficiency in at least one modern programming language (e.g., Python, Java, C#, or similar).
  • Experience with cloud platforms and services (e.g., AWS, Azure, GCP) and data pipelines for AI/ML workloads.
  • Demonstrated experience working in multi-project or portfolio environments (e.g., IDIQ, multi-TO, or large-scale programs).
  • Familiarity with DevSecOps/CI/CD practices and tools (e.g., GitLab, GitHub Actions, Jenkins, containers, Kubernetes).
  • Experience transitioning legacy applications or data systems to modern architectures.
  • Strong communication skills with the ability to explain complex AI concepts to technical and non-technical stakeholders.
  • Proven ability to balance innovation with delivery discipline in meeting cost, schedule, and performance goals.

Desired Skills and Experience


  • Advanced degree (Master’s or PhD) in a relevant technical field.
  • Experience supporting government or regulated industry customers under IDIQ or similar contract vehicles.
  • Background in MLOps and observability for AI systems (model monitoring, drift detection, logging, metrics).
  • Experience with data governance, responsible AI, and explainable AI (XAI) practices.
  • Familiarity with enterprise architecture frameworks and portfolio management.
  • Experience leading or mentoring AI/ML teams across multiple projects.

Key Competencies


  • Strategic & Systems Thinking: Ability to see across task orders and engineer shared solutions and standards.
  • Technical Leadership: Guides architecture and implementation of AI/ML capabilities, setting patterns and best practices.
  • Innovation & Continuous Improvement: Drives experimentation and adoption of modern AI and engineering practices.
  • Stakeholder Management: Engages customer and internal stakeholders effectively, managing expectations and risks.
  • Delivery Discipline: Maintains focus on cost, schedule, and technical performance across completion-based task orders.

The likely salary range for this position is $169,604 - $229,464. This is not, however, a guarantee of compensation or salary. Rather, salary will be set based on experience, geographic location and possibly contractual requirements and could fall outside of this range.

Scheduled Weekly Hours:

40

Travel Required:

None

Telecommuting Options:

Onsite

Work Location:

USA VA Chantilly

Additional Work Locations:

Total Rewards at GDIT:

Our benefits package for all US-based employees includes a variety of medical plan options, some with Health Savings Accounts, dental plan options, a vision plan, and a 401(k) plan offering the ability to contribute both pre and post-tax dollars up to the IRS annual limits and receive a company match. To encourage work/life balance, GDIT offers employees full flex work weeks where possible and a variety of paid time off plans, including vacation, sick and personal time, holidays, paid parental, military, bereavement and jury duty leave. To ensure our employees are able to protect their income, other offerings such as short and long-term disability benefits, life, accidental death and dismemberment, personal accident, critical illness and business travel and accident insurance are provided or available. We regularly review our Total Rewards package to ensure our offerings are competitive and reflect what our employees have told us they value most.

 

 


Our Identity Verification Process:

As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during virtual interviews. We reserve the right to take your picture to verify your identity and prevent fraud. By proceeding, you authorize the collection, processing, and use of your biometric data for identity verification and security purposes.

 

 

About Our Work:

We are GDIT. A global technology and professional services company that delivers technology solutions and mission services to every major agency across the U.S. government, defense and intelligence community. Our 26,000 experts extract the power of technology to create immediate value and deliver solutions at the edge of innovation. We operate across 50+ countries worldwide, offering leading mission-ready capabilities in AI, cloud, cyber and software development.

Join our Talent Community to stay up to date on our career opportunities and events at

gdit.com/tc.

Equal Opportunity Employer / Individuals with Disabilities / Protected Veterans

Skills

PythonJavaAWSAzureGCPKubernetesJenkinsCI/CDMachine LearningNLPTensorFlowPyTorchScikit-learnData ScienceData EngineeringGitHubGitLabPrototypingProgram ManagementChange Management

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