SR GEN AI Engineer

Seeking a Store AI Agent Lead to architect, build, and scale AI-powered agents supporting store operations. The role requires strong hands-on experience with Agentic AI, LLMs, RAG, vector search, AWS, and enterprise system integration, along with the ability to take solutions from architecture through production., * Lead the end-to-end architecture and implementation of Store AI Agents.

• Design agentic workflows integrating LLMs with APIs, databases, backend services, enterprise applications, and MCP servers.
• Build and optimize RAG solutions, including embeddings, retrieval, vector search, grounding, and context management.
• Define the process for onboarding and integrating new AI agents, including testing, deployment, monitoring, and production readiness.
• Establish clear architecture between LLM reasoning/generation and deterministic backend services.
• Leverage Lakehouse/Medallion architecture (Bronze, Silver, Gold) to support AI and data use cases.
• Define scalable approaches for AI/RAG testing, validation, observability, and performance optimization.
• Address production challenges including latency, context limitations, retrieval quality, scalability, and reliability.
• Provide technical leadership across AI/ML, data engineering, cloud, application, and business teams.

• Proven experience delivering at least one end-to-end LLM, RAG, or Agentic AI project.
• Strong architectural and hands-on experience with Generative AI on AWS.
• Hands-on knowledge of LLMs, RAG, embeddings, vector search, and agentic workflows.
• Experience integrating AI agents with APIs, databases, backend services, and enterprise systems.
• Understanding of MCP (Model Context Protocol) and agent-to-tool/service integration.
• Experience with Lakehouse and Medallion Architecture and data pipeline optimization.
• Strong understanding of AI testing, observability, security, scalability, latency, and production performance.
• Ability to articulate end-to-end architecture, technology choices, integration patterns, and design trade-offs.

Preferred

• Experience with AWS-based GenAI and data platforms.
• Experience building enterprise-scale AI agents or multi-agent solutions.
• Exposure to modern vector databases, Lakehouse technologies, and AI orchestration frameworks.
• Strong technical leadership and stakeholder communication skills.