AI Solutions Architect & Federal Technical Lead – US Federal

AI Solutions Architect & Federal Technical Lead - US Federal Sector

Company Overview: Over the past 15 years, eTel has delivered essential solutions for the federal government by securing and managing data, providing scalable identity access, modernizing legacy systems, and building high-performance platforms. By integrating new technologies and ensuring reliable operations we help agencies stay prepared for future challenges. As a premier technology solutions and services company to the US federal government, eTel possesses longstanding relationships across the federal civilian marketplace.

Other customers include the broader Treasury Department, Commerce Department, and State Department.

eTel offers integrated CMMI Level 3 processes, tools, and techniques with innovative, cost-efficient, and secure solutions to address complex challenges. eTel also holds ISO 9001:2015, ISO/IEC 27001:2013, and ISO/IEC 20000-1:2018 certifications, and offers dedicated subject matter experts (SMEs) and thought leaders that possess a deep understanding of customers’ environments and challenges.

Mode: Hybrid (combining remote focused engineering work with onsite collaboration at our corporate office (Herndon, VA) and executive client sites for technical briefings/deployments).

Role Overview: We are seeking a highly technical, mission-driven AI Solutions Architect & Technical Lead to drive the engineering and implementation of advanced artificial intelligence within the US Federal Government space. In this role, you will serve as the definitive technical authority, architecting and actively building modern, secure AI frameworks that drive agency transformation. You will utilize your deep understanding of legacy federal systems to design hybrid architectures, build functional proofs-of-concept (PoCs), and seamlessly bridge the gap between legacy infrastructure and cutting‑edge GenAI capabilities.

While deeply hands‑on, you will also confidently engage with Senior Executive Service (SES) members, agency CIOs, and senior government technical leaders to validate technical approaches and shape the future of federal technology.

• Act as the lead technical builder to rapidly engineer, code, and ship high‑impact AI/ML Proofs of Concept (PoCs) and pilot programs within secure federal sandbox environments.
• Develop and deploy custom Retrieval‑Augmented Generation (RAG) pipelines, fine‑tune Large Language Models (LLMs), and implement robust vector databases tailored to federal mission data.
• Bridge the gap between rigid government engineering standards and agile AI software deployment by implementing modern Dev Sec Ops  practices.
• Evaluate complex, legacy federal enterprise architectures (including monolithic databases and mainframes) to design and execute AI‑driven optimization and integration strategies.
• Design comprehensive, hybrid system blueprints that safely and effectively integrate modern cloud‑native AI solutions with siloed on‑premise government systems.
• Ensure all proposed architectures are inherently designed to strictly comply with FedRAMP, DoD Impact Levels (IL4/IL5/IL6), and Zero Trust mandates.
• Technical Strategy & Executive Advisement
• Conduct deep‑dive technical discovery sessions and briefings with SES leaders, flag officers, and agency technical directors (CIOs/CTOs).
• Translate complex mission challenges into actionable, secure technical roadmaps and system designs.
• Serve as the primary technical Subject Matter Expert (SME) and author for complex technical volumes in RFIs, RFPs, and white papers to secure prime contract vehicles.
• Compliance & Deployment Leadership
• Guide federal technical teams through the complex Authority to Operate (ATO) processes by providing comprehensive architectural documentation and security mappings.
• Architect solutions specifically tailored for high‑security, air‑gapped, or disconnected edge environments.

• Technical Skills & Hands‑On Expertise
• AI/ML Stack
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  Deep, hands‑on command of LLM orchestration (e.g., Lang Chain, Llama Index), RAG architectures, vector databases (e.g., Milvus, Pinecone, pgvector), and model fine‑tuning/deployment.
• Programming &…