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Remote role, mid-level experience band, and metro location increase applicant competition.
Strong LLM and ML specialization limits cross-industry transferability.
Many mandatory LLM-specific technologies and infrastructure skills create strict screening filters.
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Design, develop, and deploy Large Language Model-powered AI applications and agents, including Retrieval-Augmented Generation (RAG) pipelines.
Build AI workflows and integrations using frameworks such as LangChain, LlamaIndex, CrewAI, AutoGen, and deploy APIs/microservices for scalable AI solutions.
Optimize model performance, implement AI guardrails, content moderation, security best practices, and work cross-functionally to deliver production-ready AI applications.
Proficiency in Python programming.
Hands-on experience with Large Language Models (LLMs) and Generative AI technologies.
Experience with AI frameworks like LangChain, LlamaIndex, CrewAI, AutoGen and knowledge of RAG architectures and vector databases (Pinecone, Weaviate, Chroma, FAISS, Milvus).
Experience working with REST APIs, cloud platforms (AWS, Azure, or GCP), and container/CI-CD technologies like Docker and Kubernetes.
Demonstrated ability to build and deploy production-scale LLM-based AI solutions integrating multiple AI APIs and frameworks.
Experience optimizing inference performance, prompt engineering, and operational cost management in AI applications.
Comfortable working closely with product, engineering, and data teams to translate business problems into scalable AI workflows.