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Tier-1 brand, metro location, and mid-level experience raise candidate competition despite niche skills.
Specialized agentic AI and LLM integration skills moderately limit cross-industry transferability.
Explicit 4–7 years and many mandatory LLM, agent-framework, backend and infra skills imply high screening strictness.
Design, develop, and deploy autonomous AI agent systems with multi-agent workflows and orchestration using Python.
Integrate large language models (LLMs) like OpenAI and Anthropic with real-world tools, APIs, data sources, and manage prompt engineering and retrieval-augmented generation (RAG) pipelines.
Build backend microservices (FastAPI) and event-driven triggers, manage agent memory and state, and implement safety guardrails and observability for AI agents.
4-7 years of relevant experience in AI development or software engineering involving Agentic AI technologies.
Bachelor's degree required: BE/BTech/MCA/MTech/MBA with technology focus; Bachelor of Technology preferred.
Mandatory technical skills: Advanced Python (async/OOP/design patterns), familiarity with Agent frameworks (LangChain, LangGraph, AutoGen, CrewAI), LLM APIs (OpenAI, Anthropic, HuggingFace), FastAPI, PostgreSQL, Redis or similar for messaging/event queues.
Work Experience Required: 4-7 years; Notice Period: Not explicitly mentioned.
Demonstrated ability to design and architect complex autonomous AI agent workflows and multi-agent orchestration at scale.
Strong backend development experience with microservices, event-driven architecture, and database persistence tailored for AI applications.
Experience with advanced LLM integration, prompt engineering, and AI safety/guardrails indicating a mature approach to AI system reliability and compliance.