A Day in the Life:

Cloud Architecture:

• Develops strategy for public cloud platforms and designs the infrastructure necessary to support that strategy, with emphasis on secure, scalable, and fully automated deployment models.
• Provides subject matter expertise to support the evaluation of cloud service offerings, workload placement options, and architectural design decisions across approved Cloud Service Providers (Azure, GCP).
• Establishes deployment practices that enhance efficiency and maintainability.
• Assesses potential project challenges related to constraints, including risks, time, resources, cost, and scope, while actively participating in strategy development and implementation to ensure project success.
• Participates in cloud security analysis and threat mitigation activities, with a strong emphasis on identity architecture, hybrid networking, encryption, and operational security.
• Develops and establishes standards for cloud resource organization, including tagging, naming, logging, monitoring, and infrastructure patterns, and provides guidance and recommendations to agency leadership regarding cloud service selection and implementation.
• Creates, strengthens, and leads the implementation of methods and practices for cloud architecture strategy development, communication, and visualization, while recommending and driving adoption of best practices to optimize systems and ensure scalability.
• Provides senior guidance to IT and agency management on cloud budgeting, cost forecasting, and resource optimization, supporting long term planning and governance expectations. 

AI Architecture:

• Develops and maintains governance processes for AI systems and reviews proposed AI workloads for alignment with technical, security, and operational standards.
• Operates and continuously improves the AI Architecture Review pipeline, including structured intake, automated evaluation workflows, and generation of consistent, citation backed technical outputs.
• Reviews AI solution designs for technical integrity, data classification alignment, identity integration, and adherence to approved cloud services across Azure, GCP, and AWS.
• Classifies AI proposals (Custom, COTS, SaaS, Hybrid) and ensures compliance with architecture standards and source control expectations.
• Evaluates identity and access patterns for AI systems, including authentication flows, MFA, RBAC, token lifecycle expectations, and integration with enterprise identity platforms such as Okta and Microsoft Entra ID.
• Reviews Infrastructure as Code compliance, tagging strategies, naming conventions, logging requirements, and monitoring baselines for AI workloads.
• Participates in AI architecture gate reviews and produces go/no go recommendations for environment transitions across the Path to Production lifecycle.
• Collaborates with Security, Privacy, Data Governance, Identity, and Cloud Operations teams to identify and resolve architectural risks in proposed AI workloads and ensure responsible, secure use of generative AI across the enterprise. 

The job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee. Other duties, responsibilities, and activities may change or be assigned at any time. 

This position is exempt from overtime compensation for additional work hours that may be required to complete essential functions or other assigned work. Exempt employees may work more than 75 hours in a pay period without additional compensation and must report a minimum of 75 hours per pay period of work hours and/or paid leave taken to receive their base biweekly salary.

What You'll Need for Success:

Cloud Technical Skills

• Extensive knowledge of public cloud platform capabilities and configurations across Azure or GCP.
• Extensive knowledge of cloud policies, standards, procedures, and techniques used in the development of enterprise cloud architecture.
• Demonstrated experience documenting cloud architecture strategy, policy, and procedures, with emphasis on Infrastructure as Code and automation-first deployment models.
• Considerable knowledge of business drivers, technology strategy, and software architecture goals to develop and deliver clear, comprehensive technical architectures.
• Ability to formulate sound recommendations, make appropriate decisions, and initiate corrective actions across multiple projects with competing deadlines.
• Ability to articulate the potential technological and budgetary impact of cloud design decisions on the organization.
• Hands-on proficiency with Terraform and CI/CD automation.

AI Technical Skills

• Demonstrated experience designing or governing enterprise AI or Generative AI systems, including at least one production deployment using a foundation model platform (e.g., AWS Bedrock, Azure OpenAI, Google Vertex AI).
• Working proficiency with structured prompting, system prompt design, LLM evaluation, and retrieval augmented generation (RAG) approaches.
• Hands on experience with GitHub, GitHub Actions, and documentation as code workflows supporting AI governance.
• Strong understanding of AI safety practices, hallucination mitigation strategies, and responsible AI controls.
• Knowledge of government data classification and residency obligations and how they affect AI model selection and deployment decisions.
• Ability to evaluate AI vendors and foundation model services for security, responsible AI compliance, and data handling requirements.

General Required Skills

• Extensive knowledge of information technology policies, standards, procedures, and techniques used in the development of enterprise architecture.
• Ability to collaborate effectively between business units, architecture, operations, and security on the development and implementation of operational and compliance standards.
• Ability to delegate work, set clear direction, manage workflow, and coach and develop employee skill sets.
• Excellent communication, problem solving, analytical, and critical thinking skills.
• Ability to perform essential functions with or without reasonable accommodation.

A degree is not required.  However, at least 7+ years of experience applying the outlined knowledge, skills, and abilities in a similar role may be considered.  

Supervisory Responsibilities/Direct Reports: