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Metro Hyderabad, moderate employer brand, and specialized LLM/RAG skillset lead to medium competition.
Specialized LLM, RAG, and agent engineering skills make cross-industry transfer difficult, indicating high sensitivity.
Explicit 7–10 years, 3+ years LLM focus, and specific tech stack imply high strictness.
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Design and implement stateful multi-agent graphs and advanced RAG pipelines to automate complex workflows.
Build and maintain integrations and API connectors for autonomous agents to interact with databases, documents, and core systems.
Write production-grade Python code with unit tests and mentor mid-level and junior developers on multi-agent engineering patterns.
7 – 10 years in software development with at least 3 years in LLM application engineering, RAG, and agent frameworks.
Advanced proficiency in Python, PyTorch/Transformers, LangChain, and LangGraph including state machine design and parallel execution.
Experience building enterprise RAG pipelines using complex unstructured document sources such as PDFs and financial filings.
Work Location: Hyderabad, India with a Hybrid work model.
Experienced in developing scalable AI-driven automation for financial or healthcare data workflows involving multi-agent systems.
Strong software engineering discipline with expertise in async Python, REST APIs, microservices, and Git workflows.
Proven capability in mentoring engineers and producing clean, maintainable production code in complex AI application environments.