Agentic AI Architect
- Source: Naukri
- Tata Consultancy Services
- On-site
- Bengaluru
- Full-Time
- Mid level
Job Description
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 thi…
Skills
- claude-by-anthropic
- Gemini
- meta-llama
- llama
- microsoft-azure
- amazon-web-services
- bedrock
- amazon-sagemaker
- vertex
- chroma
- Milvus
- azure-search
- guardrails
- scaleai
- LangChain
- LangGraph
- crewai
- Python
- Kubernetes
- Docker
- amazon-machine-learning
- azure-databricks
- databricks
