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Mid-level Bengaluru role in a popular LLM area but requires niche agentic AI skills, yielding moderate competition.
Specialized LLM, agentic system, and cloud deployment expertise limits transferability across industries.
Many explicit years and mandatory LLM, agentic, cloud, and orchestration skills make screening highly strict.
Design, develop, and deploy multi-agent and agentic AI systems, focusing on workflow automation and autonomous decision-making.
Implement agent communication protocols, build intelligent orchestration systems, and integrate RAG workflows with enterprise applications.
Drive cloud-hosted Generative AI solutions using LLM orchestration frameworks and optimize production LLM inference with hands-on experience in AWS services.
3-6 years overall technical experience with minimum 2 years hands-on in Generative AI and LLM technologies.
At least 1 year experience building agentic systems, workflow automation, or autonomous AI applications.
Proficiency in Python required; experience with agentic frameworks (e.g., AutoGen, LangGraph), workflow orchestration tools, OpenAPI, A2A protocols, and MCP required.
Role location is Hybrid Bengaluru; no explicit mention of notice period or degree requirements.
Experienced in designing multi-agent architectures with memory, planning, and tool-use capabilities for autonomous workflows.
Skilled in deploying and fine-tuning LLM models in production, using AWS Bedrock, SageMaker, and various LLM orchestration frameworks (LangChain, LlamaIndex).
Familiar with advanced agent evaluation, testing, MLOps/LLMOps practices, containerization, and RAG architectures optimizing business processes autonomously.