Agentic AI Architect
Job Description
Position : Agentic AI Architect
Exp : 10yrs to 15yrs
Location : Bangalore
Work Mode : Hybrid(4days work from office and 1 day work from home)
Job Description
Role Summary:
We are looking for a Senior Agentic AI Architect to design and build a next-generation enterprise Agentic AI platform and solutions powering hundreds of users and complex multi-agent workflows.This role goes beyond LLM integration-you will define agentic architecture, orchestration patterns, governance frameworks, and enterprise-scale deployment strategies to enable autonomous, reliable, and explainable AI systems.You will work closely with product, engineering, and business stakeholders to transform AI from experimentation to production-grade, business-critical systems.
Responsibilities
Define end-to-end architecture for multi-agent systems (hierarchical, collaborative, autonomous agents)
Design reusable agent frameworks, templates, and SDKs
Establish agent orchestration patterns (planner-executor, tool-using agents, multi-agent coordination)
Design agent control planes (task routing, agent selection, execution flows)
Define patterns for: Human-in-the-loop, Agent supervision & escalation, Multi-agent negotiation & collaboration
Build and deploy frameworks for Agent governance & policy enforcement
Define metrics for:Agent accuracy, latency, cost, and success rate
Design Context window optimization strategies, Dynamic context injection, Memory pruning & summarization
Define agent interaction paradigms:Conversational UX, Task-driven workflows
Evaluate and leverage platforms like Azure AI Foundry / AWS Bedrock / Google Vertex AI/Langgraph
Skills & Qualifications :
Strong expertise in Generative AI, LLMs, and Agentic AI systems
Hands-on experience with agent frameworks (Microsoft Foundry agent, CrewAI, Google ADK, Langgraph)
Deep understanding of multi-agent architectures and orchestration patterns
Proficiency in Python and/or TypeScript for AI system development
Experience with cloud platforms (Azure, AWS, or Google Cloud) and AI services
Knowledge of RAG, vector databases, and context engineering techniques
Experience designing scalable, distributed, and microservices-based architectures
Strong understanding of AI governance, guardrails, and responsible AI practices
Experience with model evaluation, performance optimization, and monitoring
Ability to translate business requirements into enterprise-grade AI solutions
