Agentic AI Architect

Key Responsibilities

• Define end-to-end Agentic AI architecture frameworks leveraging LLMs, multi-agent systems, and orchestration layers
• Design autonomous AI agents capable of planning, reasoning, memory management, and tool usage
• Establish reference architectures for enterprise-grade AI applications (cloud-native, scalable, secure)
• Integrate AI agents with enterprise systems (Data Platforms, ERP, CRM, APIs, and event-driven systems)
• Build and deploy multi-agent systems using frameworks such as LangChain, Semantic Kernel, AutoGen, CrewAI, or similar
• Implement agent orchestration patterns (planner-executor, reflection loops, self-healing agents)
• Develop agents with capabilities including: Task decomposition and planning, Contextual reasoning and chaining, Memory (short-term, long-term, vector-based retrieval), Tool calling and API integrations
• Architect solutions leveraging leading LLMs (Azure OpenAI, OpenAI, Anthropic, etc.)
• Implement RAG (Retrieval-Augmented Generation) pipelines with vector databases (FAISS, Pinecone, Azure AI Search, etc.)
• Optimize prompt engineering, fine-tuning, and grounding strategies
• Ensure efficient token usage, latency, and cost optimization
• Integrate Agentic AI solutions with: Data ecosystems (Azure Databricks, Synapse, Snowflake), Workflow tools (ServiceNow, Power Platform, custom enterprise apps), APIs, microservices, and event-driven architectures
• Enable AI-driven automation across business processes

Governance, Security & Responsible AI

• Define AI governance frameworks (auditability, compliance, explainability)
• Implement guardrails for safe and responsible AI usage
• Ensure data privacy, model security, and regulatory compliance
• Design monitoring mechanisms for hallucination detection and agent reliability

Performance Optimization & Scalability

• Optimize inference performance, caching strategies, and execution flows
• Design scalable multi-agent systems across distributed/cloud environments
• Maintain throughput, reliability, and system health

Leadership & Strategy

• Lead architecture discussions with stakeholders and executive leadership
• Drive AI adoption strategy and roadmap across business units
• Mentor engineering teams on Agentic AI best practices
• Evaluate emerging tools, frameworks, and innovations in AI ecosystems