Senior Enterprise Architect (0038)

OCT Consulting • Washington, DC

1d • Remote

About The Position

OCT Consulting is a business management and technology consulting firm that supports Federal Government clients. We provide consulting services in Strategy, Process Improvement, Change Management, Program and Project Management, Acquisition and Procurement, Data Science, and Information Technology. OCT currently has an opening for a Senior Enterprise Architect to work with our DoD client. The Senior Enterprise Architect provides subject-matter expertise in system architectural development, engineering, and integration to support R&D and Production systems for our client. The primary objective is to deliver enterprise-level architecture and governance integration, ensuring the platform evolves into a scalable, secure, and sustainable environment for both AI research and production. This person will serve as the lead subject-matter expert responsible for the enterprise-level architecture of the government client’s AI platform. Primary duties include designing architectural blueprints, developing scalable data and MLOps patterns, and ensuring the platform’s architecture aligns with all enterprise governance, Responsible AI (RAI), and IL5 security requirements. The contractor serves as the primary technical authority for the platform’s design and strategic evolution. As a senior contributor in the firm, this individual will also be expected to support business development and firm activities, as needed, at the direction of contract and corporate leadership.

Requirements

• Must be a U.S. Citizen
• M.S. in Computer Science, Information Technology, Engineering, or similar
• Current TOP SECRET Clearance
• 15+ years of full-time professional work experience, 12+ years of progressive experience in enterprise-level systems architecture, engineering, and governance within the federal government, with demonstrated expertise in AI/ML platforms, MLOps, and secure (IL5) cloud environments
• AI/ML Frameworks: Proficiency in designing and maintaining architecture for both generative AI (e.g., Transformers, Large Language Models) and traditional AI workloads.
• Architectural Pattern Development: Ability to create reusable blueprints for rapid prototyping, synthetic data experimentation, and "transition-to-production" pathways.
• Data Engineering: Expertise in developing scalable patterns for ingesting and managing structured, semi-structured, and unstructured data.
• Advanced Analytics Integration: Skill in institutionalizing advanced analytics within a unified research and production environment.
• DoD Security Standards: Subject matter expertise in IL5 security requirements and the implementation of controls for handling sensitive data within secure enclaves.
• Responsible AI (RAI): Practical knowledge of applying Responsible AI lifecycle controls and enterprise data governance policies.
• MLOps Lifecycle Management: Deep understanding of institutionalizing Machine Learning Operations (MLOps), including model versioning, automated retraining, and performance monitoring.
• Scalability Design: Ability to ensure AI platforms evolve into sustainable, enterprise-level environments that support growing research demands.

Nice To Haves

• Professional certifications such as Certified Information Systems Security Professional (CISSP), TOGAF, or equivalent DoD architecture Framework (DoDAF) experience are highly desirable
• Remote role, but must be physically located in the Washington DC greater metro area; must be available for occasional client meetings

Responsibilities

• Architectural Design and Engineering
• Architecture Development: Design, document, and maintain reusable architecture and clear patterns for generative and traditional AI workloads.
• Prototyping and Production: Support rapid prototyping and synthetic-data experimentation while establishing clear, standardized pathways to transition solutions into production.
• Strategic Coherence: Provide analysis and recommendations to ensure the MAPS-RE functions as a unified environment, focusing on reducing siloed development and accelerating capability transitions.
• Governance, Security, and Compliance
• Enterprise Integration: Ensure all platform architecture aligns with enterprise data governance policies, Responsible AI (RAI) lifecycle controls, and IL5 security requirements.
• Sensitive Data Management: Define and implement governance controls specifically for the use of sensitive data within the research enclave.
• Policy Alignment: Continuously review and adjust architecture and data patterns to remain compliant with overarching enterprise policy and compliance frameworks.
• Development Guardrails and Standardization
• Citizen Development Guidance: Define and document architectural guardrails to enable "citizen development" and ensure user-created solutions comply with enterprise standards without introducing security risks.
• Intake Evaluation: Implement standardized intake and evaluation criteria for new capabilities to reduce duplication of effort across mission components.
• MLOps and Data Engineering
• Operationalization: Support the institutionalization of Machine Learning Operations (MLOps) and advanced analytics.
• Data Pipeline Patterns: Develop scalable data engineering patterns for the ingestion, processing, and management of structured, semi-structured, and unstructured data.

Benefits

• Medical, Dental, and Vision insurance
• Retirement savings 401K plan provided by an industry-leading provider with 3% employer contributions of the employee’s gross salary
• Paid Time Off and Standard Government Holidays
• Life Insurance, Short- and Long-Term disability benefits
• Training Benefits

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Number of Employees: 11-50 employees