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Job Description: Agentic AI Architect/ Manager Location: Hyderabad , Chennai , Bengaluru
Type: Full-Time
Experience Level: Senior/Lead (10+ years in AI/Software Architecture)
Role OverviewAs an Agentic AI Architect, you will be at the forefront of the next evolution of Generative AI. You will design and implement sophisticated, autonomous systems where AI agents don't just "chat," but reason, plan, use tools, and collaborate to execute complex business workflows. You will bridge the gap between high-level strategic goals and technical execution, ensuring our agentic frameworks are scalable, secure, and reliable.
Key Responsibilities- System Design: Architect multi-agent systems (MAS) using frameworks like LangGraph, AutoGen, or CrewAI to handle long-running, complex tasks.
- Reasoning & Planning: Implement advanced cognitive architectures (e.g., Chain-of-Thought, ReAct, or Tree-of-Thoughts) to improve agent autonomy and decision-making.
- Tool Integration: Design "Function Calling" and API-driven environments where agents can securely interact with enterprise databases, ERPs, and external SaaS tools.
- Governance & Safety: Establish guardrails, human-in-the-loop (HITL) protocols, and monitoring systems to ensure agentic behavior remains predictable and ethical.
- Optimization: Lead the evaluation of LLMs (GPT-4, Claude, Llama 3) for specific agentic roles, focusing on latency, cost, and context window management.
Technical Must-Haves- Frameworks: Mastery of LangChain/LangGraph, AutoGen, or Semantic Kernel.
- Vector DBs: Deep experience with Pinecone, Milvus, or Weaviate for RAG-enhanced memory.
- Orchestration: Proven ability to build "agent loops" that include self-correction and iterative refinement.
- Backend: Expert-level Python, FastAPI, and cloud-native services (Azure AI Studio, AWS Bedrock, or GCP Vertex AI).
- DevOps for AI: Experience with LLMOps, including prompt versioning, evaluation pipelines, and tracing (e.g., LangSmith, Arize Phoenix).
Preferred Qualifications- Contributions to open-source Agentic AI projects.
- Experience with Small Language Models (SLMs) for specialized, low-cost agent tasks.
- Background in Distributed Systems or Robotic Process Automation (RPA).
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