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Metro location and broad Staff title increase applicants, but niche LLM/agent expertise reduces competition.
Deep LLM/agent engineering expertise required, limiting cross-industry interchangeability.
11+ years and specialized LLM/agent skills make filters strict.
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Design, build, and deploy AI-powered applications using LLM ecosystems, Agentic AI architectures, and intelligent automation frameworks.
Lead development of Agentic AI systems, Retrieval-Augmented Generation (RAG) pipelines, multi-agent workflows, and AI orchestration integrating enterprise systems and data platforms.
Oversee production deployment, scalability, monitoring, CI/CD, cost optimization, and provide technical leadership and mentorship to AI engineering teams.
11+ years of relevant software engineering experience, explicitly in AI and LLM-powered application development.
Strong expertise in Python programming and experience with AI frameworks such as LangChain, LangGraph, LangSmith.
Experience with vector databases (e.g., Pinecone, Chroma), containerization, microservices, cloud platforms (AWS, Azure), and AI model deployment/scaling.
Not explicitly mentioned: formal degree requirements, specific location, or notice period details.
Deep technical specialization in AI-native application architecture, including multi-agent systems and RAG pipelines within enterprise contexts.
Proven ability to lead complex AI/ML production systems from architecture through deployment and ongoing observability.
Experience operating at the intersection of software engineering rigor and pioneering AI technology, with capacity to set best practices and mentor teams.