AI/ML Technical Architect Lead

🏢 General Dynamics Information Technology · all General Dynamics Information Technology jobs
📍 United States
💰 USD 204,000 - 276,000 / annual
📅 Posted 2026-08-22 · via Himalayas
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Type of Requisition:
Regular
Clearance Level Must Currently Possess:
None
Clearance Level Must Be Able to Obtain:
None Public Trust/Other Required:
BI Full 6C (T4)
Job Family:
Technical Solutions Job Qualifications:
Skills:
Artificial Intelligence (AI), Machine Learning (ML), Solution Architecture Certifications:
None Experience:
10 + years of related experience US Citizenship Required:
No
Job Description:

Own your opportunity to turn data into measurable outcomes for our customers’ most complex challenges. As an Artificial Intelligence (AI)/Machine Learning (ML) Technical Architect Lead at GDIT, you’ll power in joining our team to support the Centers for Medicare and Medicaid Services (CMS). Work Visa sponsorship will not be provided.

At GDIT, people are our differentiator. As an AI/ML Technical Architect Lead supporting CMS, you will architect, develop, integrate, and operationalize AI/ML Technical Architect Lead capabilities that enhance decision support and operational readiness across environments. You will be responsible for designing, developing and deploying AI models, algorithms and systems to enhance productivity, decision-making and automation within the organization.
Key Responsibilities

- Serve as the technical lead for AI/ML strategy, architecture, and implementation across the program.

- Design and deploy scalable AI/ML models in support of the CMS mission.

- Lead development of predictive analytics, automation frameworks, and intelligent decision‑support systems.

- Integrate AI solutions into secure enterprise and tactical environments.

- Ensure compliance with CMS cybersecurity and data governance standards.

- Provide oversight of data engineering pipelines and model lifecycle management (MLOps).

- Develop and maintain model validation, explainability, and bias mitigation practices.

- Advise program leadership and stakeholders on emerging AI technologies and mission applications.

- Support transition of experimental or prototype AI capabilities into operational production systems.

- Integrate security, ethical, and data governance requirements directly into AI development workflows, ensuring alignment with CMS Risk Management Framework expectations.

- Drive AI security risk management by assessing threats and producing required ATO, configuration management, and incident response documentation.

- Coordinate with ISSOs, business owners, and other stakeholders to implement secure AI solutions and participate in audits, interviews, and governance reviews.

- Lead engagement in security governance processes to maintain continuous compliance with CMS cybersecurity and operational standards.

- Mentor junior engineers and provide technical leadership across cross‑functional teams.

Required Qualifications

- Bachelor’s degree in Computer Science, Engineering, Data Science, Mathematics, or related technical field (Master’s or PhD preferred).

- 10+ years of progressive experience in AI/ML, data science, software engineering, or related advanced analytics disciplines, including hands‑on experience with modern AI technologies.

- This is a hands on development position must have experience developing AI/ML solutions.

- 5+ years of hands-on experience designing, developing, and deploying AI/ML solutions in production environments, including experience with modern AI technologies and MLOps practices.

- Proficiency in programming languages such as Python, R, and/or Java.

- Deep understanding of machine learning frameworks such as TensorFlow or PyTorch, preferably implemented within AWS SageMaker.

- Experience integrating AI/ML capabilities into secure enterprise environments and adhering to cybersecurity, data governance, and compliance requirements.

- Experience developing AI products or functional prototypes using Retrieval‑Augmented Generation (RAG) and agentic AI technologies.

- Experience working with cloud computing platforms (AWS preferred; Azure or Google Cloud acceptable) and usi

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