Agentic AI Solution Architect - PAN India

Job description

**Key Responsibilities** AI Solution Architecture - Design end-to-end Agentic AI architectures for enterprise use cases. - Define AI architecture standards, governance frameworks, and implementation blueprints. - Lead AI transformation and modernization initiatives. - Establish scalable and secure AI platform architecture patterns. Agentic AI & Multi-Agent Systems - Design autonomous AI agents with: - Reasoning - Planning - Memory management - Task execution - Decision-making - Define multi-agent orchestration patterns and collaboration frameworks. - Implement human-in-the-loop (HITL) validation mechanisms. - Design agent communication protocols and tool integrations. Generative AI & LLM Engineering - Evaluate and architect solutions using: - GPT - Claude - Gemini - Llama - Mistral - Open-source foundation models - Design prompt engineering and prompt orchestration frameworks. - Architect enterprise RAG solutions. - Define semantic search and vector retrieval strategies. AI Platform & Cloud Architecture - Architect solutions on: - Azure OpenAI - Azure AI Services - AWS Bedrock - Amazon SageMaker - Google Vertex AI - Integrate AI systems with enterprise applications and APIs. - Design event-driven and cloud-native AI platforms. Data & Knowledge Architecture - Architect enterprise knowledge systems. - Design vector database solutions using: - Pinecone - Chroma - Weaviate - Milvus - Azure AI Search - Define: - Data ingestion - Embeddings - Chunking - Indexing - Retrieval strategies AI Governance & Security - Establish responsible AI governance frameworks. - Implement AI security controls and model guardrails. - Manage: - Prompt injection protection - Hallucination controls - Data privacy compliance - Model governance LLMOps & AgentOps - Define deployment and operational frameworks for AI systems. - Implement monitoring and observability strategies. - Establish evaluation metrics and AI performance KPIs. - Drive continuous improvement and feedback loops. **Must-Have Skills** Agentic AI & Generative AI - Strong expertise in: - Agentic AI - Multi-Agent Systems - Generative AI - LLM Architectures - RAG Frameworks AI Frameworks - Hands-on experience with: - LangChain - LangGraph - Semantic Kernel - AutoGen - CrewAI - OpenAI APIs Cloud AI Platforms - Experience with: - Azure OpenAI - Azure AI Foundry - AWS Bedrock - Amazon SageMaker - Google Vertex AI Architecture & Engineering - Expertise in: - Solution Architecture - Microservices - REST APIs - Event-Driven Architecture Programming - Strong proficiency in: - Python AI Data Platforms - Experience with: - Vector Databases - Knowledge Graphs - Semantic Search - Embedding Models - Data Governance MLOps / LLMOps - Experience with: - Model Deployment - LLMOps - AgentOps - Kubernetes - Docker - CI/CD AI Governance & Security - Strong understanding of: - Responsible AI - Model Governance - AI Security - Compliance & Privacy Controls **Good-to-Have Skills** Certifications - Azure AI Engineer Associate - Azure Solutions Architect Expert - AWS Machine Learning Specialty - Google Professional ML Engineer - TOGAF - Certified Kubernetes Administrator (CKA) - Databricks Generative AI Certification Domain Experience - Enterprise digital transformation - Financial Services - Banking - Insurance - Large-scale AI modernization programs