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Mid-level AI role in a metro location with common experience band increases applicant competition.
Role requires specialized LLM, LangChain, and multi-agent experience, reducing transferability across non-AI roles.
Multiple mandatory skills (LLMs, LangChain, multi-agent, cloud, MLOps) and explicit 4–6 years requirement.
Design, develop, and deploy enterprise-grade AI solutions leveraging LLMs and multi-agent architectures.
Build and optimize scalable AI pipelines, APIs, and multi-agent systems using LangChain, LangGraph, MCP, and related frameworks.
Manage end-to-end AI solution lifecycle including performance, cost, and reliability optimization in production environments.
4–6 years of experience in AI/ML engineering or related roles.
Strong Python programming skills (mandatory).
Experience with LLMs, LangChain, LangGraph, multi-agent systems, and MCP or similar protocols.
Experience with deploying AI solutions on cloud platforms (Azure, AWS, or GCP).
Experienced in designing and managing multi-agent AI systems and advanced LLM orchestration.
Proficient in modern AI frameworks like LangChain and LangGraph with hands-on knowledge of RAG, embeddings, and prompt engineering.
Able to collaborate effectively with product, engineering, and data teams to translate business needs into AI solutions.