Senior AI Architect/Engineer

Technomics is a growing employee-owned, decision analytics company that specializes in cost and economic analysis to facilitate better decisions faster. We enable a wide range of clients across the Federal government, from senior level policy makers to program managers, to choose smartly, buy effectively and operate efficiently. We deliver practical, credible and defensible results offering actionable insights by applying data-driven and analytics-based approaches in combination with multidisciplinary talent, subject matter experts, and tangible and repeatable assets in the form of databases, models, approaches and techniques.

Senior Analysts have the knowledge, skills, abilities and initiative to deliver timely, practical and innovative solutions to our clients as part of high-performing project teams typically composed of a mix of junior and mid-level analysts who will look to you for technical acumen and mentoring.

Our employee-owners pride themselves on their ability to apply deep analytical rigor and innovative thought that assist clients in understanding and solving a myriad of challenging resource planning and management problems.

This position is located in Arlington, VA.

Position Overview

The Senior AI Architect/Engineer will lead the design, buildout, and operationalization of the company’s enterprise AI platform in Azure GCC High. The role will establish enterprise capabilities for secure frontier model access, RAG-enabled knowledge systems, and governed AI APIs available across the organization. The position will also enable internal engineering teams to deploy AI-powered tools, applications, and services within a controlled cloud environment. The architect will also apply their cloud and AI infrastructure expertise to support both internal initiatives and client-facing engagements.

Primary Responsibilities

Enterprise AI Platform Architecture

• Design and deploy secure AI infrastructure in Azure GCC High to support enterprise AI capabilities
• Establish enterprise access to frontier models, including RAG-enabled knowledge systems and internal chat tools
• Build and manage secure API layers that provide controlled access to approved models and AI services
• Implement governance controls including RBAC, audit logging, monitoring, and usage tracking, along with cost management and chargeback mechanisms
• Collaborate with corporate IT to configure networking, private endpoints, and identity integration required for secure enterprise deployment
• Enable engineers and technical teams with controlled environments for coding agents, containers, APIs, web applications, and AI-enabled services
• Define and maintain model lifecycle practices including evaluation, approval, deployment, and operational monitoring

AI Adoption Support

• Support integration of AI models into analytics pipelines, internal tools, and client-facing solutions
• Advise internal teams and both current and prospective clients on AI use case identification, solution design, and implementation approaches aligned to business needs
• Provide hands-on technical support for deploying AI-enabled applications, including prototyping, troubleshooting, and performance tuning