Agentic AI

5 days ago

Bengaluru Hyderabad Pune, India Brillio Full time ₹ 20,00,000 - ₹ 50,00,000 per year

Primary - Lang Graph, ReAct, LangChain, LlamaIndex, Python(Frameworks) (ML Model frameworks)

Secondary - GCP, Google Spanner/Neo4j, CrewAI, AutoGen, OpenAI

JD:

The Agentic AI Lead is a pivotal role responsible for driving the research, development, and deployment of semi-autonomous AI agents to solve complex enterprise challenges. This role involves hands-on experience with LangGraph, leading initiatives to build multi-agent AI systems that operate with greater autonomy, adaptability, and decision-making capabilities.

The ideal candidate will have deep expertise in LLM orchestration, knowledge graphs, reinforcement learning (RLHF/RLAIF), and real-world AI applications. As a leader in this space, they will be responsible for designing, scaling, and optimizing agentic AI workflows, ensuring alignment with business objectives while pushing the boundaries of next-gen AI automation.

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Key Responsibilities:

  1. Architecting & Scaling Agentic AI Solutions

  2. Design and develop multi-agent AI systems using LangGraph for workflow automation, complex decision-making, and autonomous problem-solving.

  3. Build memory-augmented, context-aware AI agents capable of planning, reasoning, and executing tasks across multiple domains.

  4. Define and implement scalable architectures for LLM-powered agents that seamlessly integrate with enterprise applications.

  5. Hands-On Development & Optimization

Develop and optimize agent orchestration workflows using LangGraph, ensuring high performance, modularity, and scalability.

  • Implement knowledge graphs, vector databases (Pinecone, Weaviate, FAISS), and retrieval-augmented generation (RAG) techniques for enhanced agent reasoning.

  • Apply reinforcement learning (RLHF/RLAIF) methodologies to fine-tune AI agents for improved decision-making.

  • Driving AI Innovation & Research

  • Lead cutting-edge AI research in Agentic AI, LangGraph, LLM Orchestration, and Self-improving AI Agents.

  • Stay ahead of advancements in multi-agent systems, AI planning, and goal-directed behavior, applying best practices to enterprise AI solutions.

  • Prototype and experiment with self-learning AI agents, enabling autonomous adaptation based on real-time feedback loops.

  • AI Strategy & Business Impact

  • Translate Agentic AI capabilities into enterprise solutions, driving automation, operational efficiency, and cost savings.

  • Lead Agentic AI proof-of-concept (PoC) projects that demonstrate tangible business impact and scale successful prototypes into production

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