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 integrationyou 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