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 solid 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.

📌 Agentic AI Engineer (Hyderabad)
🏢 Tata Consultancy Services
📍 Hyderabad