Washington, District of Columbia, United States of America
Full Time
10 hours ago
$175,000 - $195,000 USD
No Visa Sponsorship
Key skills
CloudTypeScriptRAIMachine LearningMLGenerative AILarge Language ModelsMLOpsData EngineeringAnalyticsLeadershipPrototyping
About this role
Role Overview
Provide subject-matter expertise in system architectural development, engineering, and integration for R&D and Production systems.
Deliver enterprise-level architecture and governance integration for AI research and production.
Design architectural blueprints and develop scalable data and MLOps patterns.
Ensure architecture aligns with enterprise governance, Responsible AI, and IL5 security requirements.
Act as the primary technical authority for the platform’s design and strategic evolution.
Support business development and firm activities as directed by leadership.
Requirements
Must be a U.S. Citizen
M.S. in Computer Science, Information Technology, Engineering, or similar
** Current SECRET Clearance (TS Preferred)**
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.
Preferred Certs: 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**
Tech Stack
Cloud
TypeScript
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