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Metro location, mid-level (3+ years) role, and hot GenAI specialization increase competition.
GenAI/LLM skills are specialized yet transferable across industries, implying moderate sensitivity.
Requires explicit 3+ years plus hands-on LLM, agent frameworks, Python, SQL and governance knowledge.
Build, deploy, and iterate AI-powered features like copilots, summarization, classification, routing, and Q&A to improve internal workflows and employee productivity.
Develop knowledge-based agents using Retrieval-Augmented Generation (RAG) and design conversational flows for internal functions such as HR helpdesk, including operational agentic or predictive models under guidance.
Manage AI product feature backlog, coordinate user acceptance testing (UAT), monitor quality and performance, and maintain supporting documentation for deployed AI solutions.
Minimum 3 years of experience in software engineering or applied solutions development (or equivalent practical experience).
Proficiency in Python, API integrations; working knowledge of SQL and data access patterns.
Familiarity with large language models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), and agent frameworks like LangChain, LlamaIndex, or Semantic Kernel.
Bachelor's degree in Computer Science, Engineering, or related field (or equivalent practical experience).
Focused on delivering working AI solutions rapidly and iterating based on user feedback rather than theoretical research.
User-centered with experience mapping workflows and improving productivity in enterprise environments.
Pragmatic technologist valuing simple, reliable solutions, operational reliability, security compliance, and quality production standards.