About the role
Job Title: Agentic AI Architect
Exp : 10+ Years
Job Description:
- Architect and implement agentic GenAI systems using modern LLM orchestration frameworks (LangChain, LangGraph, CrewAI, AutoGen, etc.).
- Design multi-agent architectures including planner–solver patterns, hierarchical agents, autonomous teams, and goal decomposition workflows.
- Define end-to-end GenAI architecture covering model selection, orchestration, memory, tools, security, observability, and deployment.
- Build reusable agent tooling, APIs, and memory architectures for coordination, context persistence, and scalable interaction.
- Lead hands-on development and production deployment of GenAI applications such as assistants, copilots, workflow automation, and decision-support systems.
- Evaluate, integrate, and optimize LLMs and multimodal models (OpenAI, Claude, Gemini, Mistral, LLaMA, etc.) and RAG pipelines using vector databases and retrieval systems.
- Optimize systems for performance, reliability, scalability, cost efficiency, and responsible AI constraints (security, privacy, bias, hallucinations).
- Establish and enforce GenAIOps / LLMOps practices including evaluation, monitoring, logging, feedback loops, and continuous improvement.
- Guide and mentor teams on agent design patterns, prompt engineering, tool abstraction, fine-tuning, and best practices.
- Partner with product, business, and domain stakeholders to translate business requirements into scalable agent-based solutions and AI roadmaps.
- Drive technology strategy and innovation by tracking advances in multi-agent systems, cognitive architectures, and open-source AI frameworks.