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What you'll do:
- Define and evolve enterprise AI architecture patterns for LLM integration, RAG, agentic workflows, and prompt orchestration.
- Design and build reusable AI components and shared platform services for observability, logging, and lifecycle management.
- Architect engineering controls for responsible AI, access management, and governance compliance.
Required qualifications:
- Progressive experience in enterprise software engineering and AI platform engineering.
- Deep understanding of generative AI, LLM integration, RAG architectures, and agentic AI patterns.
- Experience designing shared platform services and reusable component libraries used by multiple teams.
Preferred qualifications:
- Experience in regulated, defense-adjacent, or security-sensitive environments.
- Background in MLOps, AI observability, and model evaluation frameworks.
- Track record of mentoring engineers and raising technical standards.
Shield AI
Shield AI is a venture-backed defense-tech company that builds intelligent systems to protect service members and civilians with products like Hivemind autonomy software and V-BAT aircraft. The company has offices worldwide and a culture that emphasizes innovation and mission impact.