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Mid-level AI engineer in a metro with broad LLM requirements draws high applicant competition.
Role requires specialized LLM, RAG, agent and cloud expertise, so backgrounds must be ML/AI focused.
Explicit 3–5 years plus mandatory LLM, LangChain, Vertex/Azure and production experience increases strictness.
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Design and develop production-grade AI systems powered by large language models (LLMs) and AI agents for real-world applications.
Build and orchestrate complex agent workflows and implement human-in-the-loop (HITL) systems for controlled AI decision-making.
Ensure system reliability, observability, safety (guardrails), and quality evaluation of AI applications at scale, collaborating with platform, data, and product teams.
3–5 years of experience in AI/ML or backend engineering.
Strong programming skills in Python and hands-on experience with LLMs, NLP, LangChain, LangGraph, RAG systems, and HITL workflows.
Proficiency with cloud platforms (GCP or Azure), specifically experience with Vertex AI and/or Azure AI Foundry.
Experience implementing AI safety mechanisms, evaluation frameworks, and scalable system design including APIs and microservices.
Experienced AI engineer with strong operational focus on deploying and maintaining scalable, secure, and observable LLM-powered AI applications in production environments.
Skilled in advanced retrieval augmentation techniques, multi-agent orchestration frameworks (e.g., MCP), and human-in-the-loop AI workflows.
Comfortable working cross-functionally with platform, data, and product teams to deliver end-to-end AI solutions within cloud infrastructure.