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Mid-level AI role with metro location and generalist AI title increases qualified applicant density.
Specialized LLM and production ML skills are transferable across industries but require domain-specific experience.
Explicit years requirement, master's degree, and mandatory LLM/MLOps tech stack enforce strict filtering.
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Design, develop, and deploy Retrieval-Augmented Generation (RAG) pipelines and AI agents for enterprise applications.
Build, optimize, and maintain scalable AI solutions in production environments using frameworks like LangGraph, AutoGen, or similar.
Collaborate with cross-functional teams to integrate AI into products and research new AI/LLM techniques to improve system performance.
Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or related field.
3-6 years of industry experience in AI or software development.
Strong software development skills including Python, APIs, microservices, and cloud deployment.
Experience with LLMs, vector databases, embeddings, orchestration frameworks, and familiarity with LangChain, LangGraph, AutoGen, or similar ecosystems.
Experienced in building and scaling AI applications in production with knowledge of data pipelines and MLOps.
Proficient in designing and deploying complex AI systems with familiarity in distributed systems and large-scale data processing.
Capable of working cross-functionally and advancing AI capabilities through research and prototype development, particularly in generative AI and intelligent agents.