Agentic AI Architect

Agentic AI Architect

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.

Key skills/competency

• Agentic AI Architect
• Generative AI
• LLMs
• Multi-agent Systems
• Orchestration Patterns
• Agent Frameworks
• Python
• TypeScript
• Cloud Platforms
• AI Governance