AI Solution Lead W2

Must have MCP and Agentic Commerce experience

REQUIRED QUALIFICATIONS 10 years of software engineering experience, with at least 3 years architecting LLM-based or agentic AI systems in production. Deep hands-on expertise with LangChain, LangGraph, RAG, MCP, prompt engineering, context engineering, and token optimization. Strong programming skills in Python and TypeScript (Java a plus); proven ability to design and implement microservices with FastAPI, Spring Boot, or Node.js. Production experience with cloud platforms (AWS, Azure, or Google Cloud Platform), Kubernetes, Docker, Terraform, and CI/CD pipelines. Solid grounding in MLOps model training/fine-tuning, evaluation pipelines, drift detection, and observability for AI systems. Track record of solution architecture for enterprise clients translating business problems into reference architectures and shipping production outcomes. Bachelor's degree in Computer Science, Engineering, or a related field.

Experience designing AI solutions for retail and e-commerce personalization engines, conversational shopping assistants, product-catalog and price-intelligence agents, demand forecasting, and store- operations automation. Familiarity with retail data ecosystems (POS, OMS, PIM, loyalty, omnichannel inventory, customer-360) and grounding LLM agents on transactional and behavioral signals. Awareness of retail trust and compliance concerns PCI-DSS, GDPR / regional consumer-data laws, and brand-safety guardrails for customer-facing agents. Experience in BFSI, payments, or other regulated industries (KYC/AML, audit & compliance, fraud and risk). Familiarity with API gateways (Apigee, Kong), developer portals, and exposure to Claude Code, Cursor, or similar agentic coding environments.