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Lead AI Architect/Strategist
At a Glance
- Location
- United States
- Work Regime
- remote
- Experience
- 10+ years
- Posted
- 2026-07-29T12:54:06-04:00
Key Requirements
Required Skills
Certifications
- TOGAF
Domain Knowledge
- Automation
- Engineering
- Government
- Healthcare
Benefits & Perks
ls and technologies Comprehensive benefits for you and your family A career path t
Requirements
10+ years of experience in software engineering, enterprise architecture, solution architecture, data architecture, or technology transformation.
5+ years of experience designing and implementing AI/ML solutions, AI platforms, or intelligent automation solutions.
Strong experience architecting enterprise-scale technology solutions and distributed systems.
Proven experience with Generative AI, Large Language Models (LLMs), and AI application architectures.
Hands-on experience with AI concepts and technologies including Retrieval-Augmented Generation (RAG), AI Agents / Agentic AI, prompt engineering, vector databases and embeddings, model orchestration, AI governance and lifecycle management
Experience with cloud AI platforms such as: Azure OpenAI / Azure AI Services, AWS Bedrock, Google Vertex AI
Compensation & Benefits
The Opportunity to support high-visibility federal missions
A culture that values innovation, growth, and collaboration
Access to cutting-edge tools and technologies
Comprehensive benefits for you and your family
A career path that rewards ambition and performance
If you’re ready to push boundaries, sharpen your skills, and join a team that is passionate about building what’s next, we’d love to meet you. Apply today and let’s build a future together!
Responsibilities
Define and execute AI architecture strategies, technical roadmaps, and modernization approaches aligned with organizational goals.
Design scalable AI platforms and solutions leveraging Generative AI, LLMs, RAG, AI agents, machine learning, and automation capabilities.
Architect intelligent AI systems that integrate models, data platforms, enterprise applications, and APIs.
Develop architecture patterns and best practices for: LLM-based applications, Agentic AI workflows, AI copilots and automation solutions, knowledge retrieval systems, data-driven decision support
Design and evaluate RAG architectures, including data ingestion, embeddings, vector search, retrieval strategies, and model orchestration.
Lead technical evaluations of emerging AI technologies, frameworks, and platforms.