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Mid-level LLM role in metro at a known global employer with broad requirements increases applicant competition.
AI/LLM engineering skills are broadly transferable across industries, so background sensitivity is low.
Explicit 4–7 years plus mandatory LLM, LangChain, vector DB and Python requirements increase filter strictness.
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Build and integrate AI-powered features and solutions into web and enterprise applications, developer tools, and business workflows.
Design scalable AI architectures including AI agents, Retrieval-Augmented Generation (RAG) systems, and workflow orchestration for production deployment.
Collaborate with architects and product teams to embed AI capabilities and optimize for performance, reliability, and cost.
4–7 years of software engineering and/or AI development experience.
Hands-on experience with Large Language Models (LLMs) such as GPT, Claude, Gemini, or open-source models.
Strong proficiency in Python and experience with AI frameworks like LangChain, LangGraph, Semantic Kernel, CrewAI, or AutoGen.
Experience with RAG, Vector Databases, Embeddings, Semantic Search, Prompt Engineering, and integrating AI APIs into production systems.
Operates with a combined mindset of consultant, architect, and builder to convert AI ideas into scalable, production-ready solutions.
Experienced in designing AI workflows and embeds AI deeply into developer tools or platforms, prioritizing measurable business impact.
Proficient in evaluating emerging AI technologies and creating intelligent automation and AI-driven developer experiences.