Senior AI Solutions Architect, Generative AI

Amentum is a global leader in advanced engineering and innovative technology solutions, trusted by the United States and its allies to address their most significant and complex challenges in science, security and sustainability. Our people apply undaunted curiosity, relentless ambition and boundless imagination to challenge convention and drive progress. Our commitment s are underpinned by the belief that safety, collaboration and well-being are integral to success.

Headquartered in Chantilly, Virginia, we have approximately 50,000 employees in more than 70 countries across all 7 continents.

The Senior AI Solutions Architect — Generative AI is the senior technical leader for the AI Center of Excellence's (AI COE) Generative AI and large language model (LLM) architecture. The role translates Amentum's AI strategy into working capabilities — designing, prototyping, and deploying GenAI solutions that drive waves of pilots projects ("lighthouse") to delivery and seed reusable patterns.

This role is expected to operate as a senior technical lead for the COE's GenAI architecture and to grow into broader COE technical leadership responsibilities over the first 6–12 months.
This role is Hybrid to our Reston, VA office and US Citizenship is required.

• Architect and deploy GenAI components for lighthouse AI projects.

• Stand up the COE's GenAI reference architecture (RAG, agent orchestration, model routing, evaluation, and guardrails) on Amentum's two-cloud posture (Azure Commercial for COE, Azure Gov for customer‑mandated programs).

• Evaluate and recommend GenAI tools, models, and platforms; lead vendor technical evaluation across the multi‑vendor RFI process.

• Grow into broader COE technical leadership responsibilities — including spoke‑team technical mentorship and AI Advisory Council technical readiness — over the first 6–12 months.

• Design, develop, and deploy GenAI / LLM‑based solutions to production for initial lighthouses, with measurable execution criteria.

• Build and prototype AI applications that support enterprise, mission, and customer‑facing use cases.

• Work hands‑on with foundation models, agent frameworks, RAG architectures, fine‑tuning approaches, and evaluation harnesses.

• Collaborate with the AI Solutions Architect — Programs & Delivery (peer role) on JANUS‑tracked delivery and Council package preparation.

• Integrate GenAI solutions into enterprise systems, mission workflows, and the AI platform under construction.

• Contribute to the COE's reusable assets library, technical patterns, and AI engineering best practices — including responsible AI, model security, and governance.

• Lead technical evaluation of vendor capabilities through the multi‑vendor RFI and Forward Deployed Engineering engagements.

• Mentor spoke‑team technical leads and operating‑group AI developers across the organization.

• Senior technical judgment — ability to architect end‑to‑end AI systems with attention to performance, cost, security, and maintainability.

• Track record of leading technical delivery in cross‑functional environments.

• Strong communicator — able to explain technical tradeoffs to executive and business audiences.

• Comfortable in ambiguity; able to set technical direction and bring others along.

• Typically 8+ years of progressive experience in AI development, machine learning engineering, or applied AI; 3+ years hands‑on with Generative AI / LLM systems with a Bachelor's degree in Computer Science, Engineering, Data Science, or related field. Master's or Ph.D. preferred.

• Production experience deploying Generative AI / LLM applications, including RAG, agentic workflows, and tool‑use patterns.

• Hands‑on AI/ML solution development across the full lifecycle — design, training/fine‑tuning, evaluation, deployment, and monitoring.

• Knowledge of AI frameworks (PyTorch, Lang Chain, Llama Index, Semantic Kernel, or equivalents) and foundation‑model ecosystems (Azure OpenAI, AWS Bedrock, open‑source).

• Experience with AI pipelines, vector databases, and data engineering for AI workloads.

• Cloud‑native architecture experience on Azure (preferred), AWS, or GCP.

• US…