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Mid-level AI title in a metro location with broad LLM requirements increases applicant competition.
Specialized LLM, RAG, and AI infrastructure skills restrict transferable fit across industries.
Explicit 3+ years plus mandatory LLM, RAG, vector DB, cloud and container skills.
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Design, build, and deploy AI-powered applications using Large Language Models, multimodal AI, and intelligent agents for enterprise workflows and customer experiences.
Develop, validate, and productionize advanced AI solutions including prompt engineering, RAG pipelines, multi-agent systems, and integration with enterprise platforms.
Optimize and maintain AI application performance, reliability, scalability, and compliance, collaborating with cross-functional teams to deliver production-grade AI products.
3+ years experience in AI, machine learning, or backend software development.
Strong proficiency in Python and experience with Large Language Models, prompt engineering, RAG, and AI agent frameworks.
Experience with AI frameworks like LangChain, LlamaIndex, CrewAI, or similar, and familiarity with vector databases (e.g., Pinecone, Weaviate).
Experience integrating AI with REST APIs, databases, cloud platforms (AWS, Azure, GCP), and knowledge of Docker, Kubernetes, and CI/CD best practices.
Experienced in building scalable, production-ready AI applications focused on enterprise use cases with measurable business impact.
Comfortable working across AI model development, system integration, and infrastructure optimization in a fast-paced, startup environment.
Capable of independent ownership and connecting technical solutions to strategic business outcomes while collaborating with multidisciplinary teams.