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Mid-level Bangalore ML role with in-demand LLM/RAG skills yields medium competition density.
Specialized LLM/RAG and agentic AI experience required, limiting easy cross-industry transfers (high).
Explicit 5–7 years plus mandatory LLM, LangChain, FastAPI, and Kubernetes requirements make shortlisting strict (high).
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Design and build production-grade Retrieval-Augmented Generation (RAG) pipelines and fine-tune large language models (LLMs) powering AI-driven voice and chat bot products for enterprise clients.
Architect, develop, test, and deploy scalable RESTful APIs using FastAPI with full lifecycle ownership, ensuring Ai model productionization on Kubernetes infrastructure.
Collaborate with cross-functional teams to define AI architecture, develop multi-step agentic AI workflows using LangChain/LangGraph, and directly impact AI product outcomes at scale.
5–7 years of Python engineering experience with hands-on RAG application development and LLM fine-tuning in production environments.
Proficient with FastAPI and databases including MongoDB, PostgreSQL, and MySQL.
Experience with Kubernetes and production deployment of AI models.
Work Location: Bangalore; Onsite 5-days/week required.
Demonstrated expertise building multi-step agentic AI systems using LangChain and/or LangGraph, not just theoretical knowledge.
Strong system design skills tailored to high-volume, enterprise-scale AI workloads.
Proven end-to-end ownership delivering and maintaining AI-powered conversational products, with ability to manage reliability and performance at scale.