We are seeking a highly experienced Senior Generative AI Engineer with expertise in Agentic AI, AI Agent Frameworks, RAG, MCP, and enterprise-scale LLM solutions. The candidate will lead the design, development, and deployment of advanced AI systems, multi-agent architectures, and intelligent automation solutions leveraging modern GenAI technologies.
9-11 years of software engineering experience
Strong hands-on expertise in Generative AI and LLM-based applications
Experience designing and implementing Agentic AI solutions
Hands-on experience with Agent Frameworks such as:
LangGraph
CrewAI
AutoGen
Semantic Kernel
LangChain Agents
Strong expertise in RAG (Retrieval-Augmented Generation)
Experience implementing MCP (Model Context Protocol)
Strong Python programming skills
Experience with OpenAI, Azure OpenAI, Claude, Gemini, Llama, or similar LLMs
Expertise in Vector Databases (Pinecone, ChromaDB, Weaviate, FAISS, Azure AI Search)
API and Microservices development experience
Roles & Responsibilities
Architect and build enterprise-grade Agentic AI platforms and solutions.
Design multi-agent orchestration workflows for business use cases.
Develop and optimize advanced RAG pipelines using enterprise knowledge repositories.
Implement MCP-based integrations between AI agents, tools, and enterprise systems.
Lead LLM solution design, deployment, scalability, and performance optimization.
Build reusable AI accelerators, frameworks, and components.
Guide development teams on GenAI best practices and AI architecture patterns.
Collaborate with business stakeholders to define AI roadmaps and use cases.
Ensure Responsible AI, security, governance, and compliance standards are followed.
Mentor junior engineers and conduct technical reviews.
Gen AI, Agent Frameworks, Agentic AI, RAG, MCP
Preferred Skills
Azure OpenAI
AWS Bedrock
Databricks Mosaic AI
GraphRAG
Knowledge Graphs
LLMOps/MLOps
Docker & Kubernetes
MLflow, LangSmith, PromptFlow
CI/CD and Cloud Platforms (Azure/AWS/GCP)
Source: Infosys careers — Read the original posting and apply
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