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Mid-level metro role with broad LLM requirements and a generalist AI Engineer title drives high competition.
Core LLM, RAG, and vector DB skills are highly transferable across industries.
Explicit years plus mandatory LLM, LangChain, RAG, embeddings, and Python requirements make shortlisting strict.
Design, develop, and deploy production-grade AI applications focused on Large Language Models (LLMs), including multi-agent workflows and Retrieval Augmented Generation (RAG) systems.
Lead efforts in LLM fine-tuning, prompt engineering, and use AI-powered coding tools to build and integrate full-stack software (frontend and backend).
Collaborate closely with US-based teams and manage integration of Python-based AI modules with Java services using multi-threading where applicable.
Undergraduate degree in Computer Science or similar engineering discipline.
5+ years of professional software development experience, including minimum 2 years with AI/ML development focused on Large Language Models.
Proficient in Python and experienced with major LLM APIs, LangChain/LangGraph frameworks, RAG architectures, vector databases, and prompt engineering.
Willingness to work overlapping hours with US time zones; Hybrid work with 2-3 days/week office presence applicable only for certain global locations (not India).
Experienced AI/ML engineer with deep practical expertise specifically in LLM integration, fine-tuning, and building agentic workflows using LangChain/LangGraph.
Comfortable owning end-to-end product development including frontend and backend, leveraging AI coding assistants for efficient delivery.
Collaborates effectively across distributed teams and handles ambiguity to build production-ready AI-first software solutions.