AI​/ML & Data Architect

Job Description

Our client is a nationally respected provider of health, science, and technology solutions supporting clients in the government and commercial sectors. They provide comprehensive enterprise information technology, strategic sourcing, and management solutions to DoD and federal civilian agencies in 40 states.

Candidate must be a U.S. Citizen or Green Card holder due to federal contracting requirements and have the ability to pass a Public Trust background investigation.

Our client is currently seeking a Full‑Time Mid to Senior Level AI/ML & Data Architect to support the development and maintenance of the CMS enterprise and project level data architecture products within the Centers for Medicare & Medicaid Services (CMS). This role will help define and implement CMS's data and AI strategies by contributing to architectural artifacts, data modeling, metadata management, and governance practices, ensuring alignment with CMS's Enterprise Architecture (EA) and Data Management policies.

Qualified candidates are urged to apply to learn more about this great opportunity!

• Assist in the documentation of data and technical related policies, standards, and procedures.
• Prepare and conduct customer presentations and briefings.
• Design and maintain logical and conceptual data models in support of CMS enterprise and project-level initiatives.
• Work closely with Chief Enterprise Architect on Artificial Intelligence, Enterprise and Data Architecture, and Technical Reference Architecture.
• Support data integration and Artificial Intelligence (AI) / Large Language Model (LLM) evolution within organization's Enterprise Architecture.
• Develop data and other architecture products such as data flow diagrams, data dictionaries, and canonical data models to support modernization and interoperability.
• Collaborate with CMS stakeholders, enterprise architects, and system owners to identify data requirements and align them with enterprise standards.
• Ensure compliance with CMS EA Framework, including integration with CEDAR and support for the CMS Business Reference Model (BRM) and Information Reference Model (IRM).
• Support metadata and master data management initiatives in coordination with the Enterprise Data Group (EDG).
• Provide technical advice on Artificial Intelligence, Machine Learning, High Performance Computing, containerization, dynamic scaling, blockchain and other advanced technology development.
• Provide architectural guidance for data integration, data sharing, interoperability, and data quality best practices.

• Education, Certifications and Years of Experience
  • Bachelor's degree in Information Systems, Computer Engineering/Science, Data Science, or a related field.
• Required Experience
  • 3+ years experience in Artificial Intelligence/Machine Learning.
  • 5+ years of experience in data architecture, data modeling, or enterprise data design.
  • Hands‑on experience designing and maintaining logical and conceptual data models, including the creation of data flow diagrams, data dictionaries, and data models.
  • Experience in designing and managing enterprise‑level data infrastructure (databases, data warehouses, data lakes) and developing blueprints/frameworks for data storage, integration, and access across large organizations.
  • Experience working with relational and non‑relational databases (e.g., Oracle, SQL Server, Postgre
    
    SQL, Mongo
    
    DB).
  • Practical experience in integrating disparate data sources and supporting data modernization and interoperability initiatives.
  • Experience in the development and documentation of data‑related policies, standards, and procedures, ensuring alignment with enterprise and federal requirements.
• Required Knowledge, Skills, and Abilities
  • Familiarity in data modeling tools such as Sparx Enterprise Architect, Prolaborate, IBM Data Architect, or ERwin.
  • Familiarity with enterprise architecture frameworks such as FEAF, Archi Mate, or DODAF.
  • Understanding of CMS data domains, healthcare data standards, or government data governance practices (preferred).
  • Knowledge of federal data strategy and compliance requirements (e.g., HIPAA,…