Agentic AI Architect

We are seeking an experienced Agentic AI Architect to lead the design and implementation of enterprise-scale AI solutions powered by Generative AI, LLMs, Agentic AI, Multi-Agent Systems, and RAG architectures. The ideal candidate will architect intelligent AI ecosystems capable of autonomous reasoning, planning, decision-making, workflow orchestration, and business process automation while ensuring security, governance, scalability, and responsible AI practices.

Key Responsibilities

AI Solution Architecture

• Design end-to-end Agentic AI architectures for enterprise business use cases.
• Develop scalable, secure, and reusable AI architecture frameworks and patterns.
• Define enterprise AI reference architectures, standards, and governance models.
• Lead AI modernization and digital transformation initiatives.

Agentic AI & Multi-Agent Systems

• Design autonomous AI agents capable of planning, memory management, reasoning, and task execution.
• Build multi-agent orchestration frameworks using modern Agentic AI platforms.
• Implement agent collaboration, tool calling, workflow automation, and decision-making capabilities.
• Design Human-in-the-Loop (HITL) mechanisms for governance and validation.

Generative AI & LLM Engineering

• Evaluate, deploy, and optimize LLMs including GPT, Claude, Gemini, Llama, Mistral, and open-source models.
• Design advanced prompt engineering, prompt chaining, and agent workflow frameworks.
• Architect Retrieval-Augmented Generation (RAG) solutions.
• Implement semantic search, vector retrieval, embeddings, and knowledge systems.
• Establish LLM evaluation and optimization strategies.

Cloud & AI Platform Engineering

• Architect AI solutions using:

• Azure OpenAI

• Azure AI Foundry

• AWS Bedrock

• Amazon SageMaker

• Google Vertex AI

• Integrate AI agents with enterprise applications, APIs, data platforms, and business workflows.

• Design event-driven and microservices-based AI architectures.

Data & Knowledge Management

• Design enterprise knowledge repositories and AI knowledge management frameworks.
• Implement vector databases including Pinecone, Weaviate, Chroma, Milvus, and Azure AI Search.
• Define ingestion, chunking, indexing, embedding, and retrieval strategies.
• Ensure data governance, lifecycle management, and knowledge quality standards.

AI Governance & Security

• Define Responsible AI governance frameworks.
• Implement AI guardrails, security controls, and compliance mechanisms.
• Address risks related to hallucinations, prompt injection attacks, data privacy, and regulatory compliance.
• Establish enterprise AI governance and model risk management practices.

LLMOps / AgentOps / MLOps

• Design and implement AI deployment pipelines and automation frameworks.
• Establish observability, monitoring, and AI performance evaluation frameworks.
• Define AI KPIs, operational metrics, and continuous improvement processes.
• Support production-scale AI operations and governance.

Required Skills

• 8+ years of overall IT experience.

• Minimum 3+ years of experience in Generative AI or AI Architecture roles.

• Strong expertise in:

• Agentic AI

• Multi-Agent Systems

• Generative AI

• LLM Architectures

• Machine Learning

• Deep Learning

• RAG Architectures

• Hands-on experience with:

• LangChain

• LangGraph

• Semantic Kernel

• CrewAI

• AutoGen

• OpenAI APIs

• Azure AI Foundry

• Strong proficiency in:

• Python

• REST APIs

• Microservices

• Event-Driven Architecture

• Experience working with:

• Azure OpenAI

• Azure AI Services

• AWS Bedrock

• Amazon SageMaker

• Google Vertex AI

• Experience with:

• Kubernetes

• Docker

• CI/CD

• Infrastructure as Code

Preferred Skills

• Knowledge Graphs and semantic reasoning systems.
• Enterprise Architecture and Digital Transformation experience.
• AI Security and Responsible AI frameworks.
• Data Governance and Regulatory Compliance.
• LLMOps, AgentOps, and MLOps implementation experience.
• Financial Services, Insurance, Healthcare, or Enterprise Platform experience.

Preferred Certifications

• Microsoft Certified: Azure AI Engineer Associate
• Microsoft Certified: Azure Solutions Architect Expert
• AWS Certified Machine Learning Specialty
• Google Professional Machine Learning Engineer
• Databricks Generative AI Certification
• TOGAF Certification
• Certified Kubernetes Administrator (CKA)

Desired Candidate Profile

• Strategic thinker with strong AI architecture expertise.
• Experience leading enterprise AI transformation initiatives.
• Ability to engage with CXOs and senior business stakeholders.
• Strong leadership, mentoring, and team-building capabilities.
• Excellent analytical, communication, and problem-solving skills.
• Proven track record delivering enterprise-scale Generative AI and Agentic AI solutions.