Senior GenAI Engineer (Agentic AI | RAG | MCP | Python)

Job Title: Senior GenAI Engineer (Agentic AI | RAG | MCP | Python)

Designation: Technology Lead

Experience: 5–10 Years

Location: Any city in India where Infosys has an office

Role Overview

We are seeking a highly skilled and hands-on Senior GenAI Engineer to architect, build, and scale enterprise-grade Agentic AI systems, Retrieval-Augmented Generation (RAG) pipelines, and Model Context Protocol (MCP) integrations.

This role demands strong engineering depth, product ownership mindset, and the ability to collaborate across business, data, and platform teams to deliver production-ready AI solutions.

Key Responsibilities

• Design and implement multi-agent systems using frameworks such as LangGraph, LangChain Agents, AutoGen, CrewAI, and LlamaIndex.
• Architect and deploy scalable RAG pipelines (chunking strategies, embeddings, vector stores, hybrid search, re-ranking).
• Implement and integrate Model Context Protocol (MCP) tools and services.
• Develop robust, production-grade Python codebases, SDKs, APIs, and deployment pipelines.
• Integrate with vector databases such as FAISS, Chroma, Pinecone, Redis, and Milvus.
• Work with leading model APIs (OpenAI, Azure OpenAI, Claude, Gemini, Llama, etc.).
• Implement observability frameworks (tracing, logging, telemetry) and safety guardrails (validation, rate limits, compliance controls).
• Conduct offline and online evaluations including unit testing, A/B testing, and performance metric tracking.
• Collaborate with cross-functional stakeholders to translate business requirements into scalable AI architectures.
• Ensure adherence to security, data privacy, governance, and AI safety standards.

Required Qualifications

• Strong expertise in Python programming and system design.
• Hands-on experience with agent frameworks (LangGraph, LangChain Agents, AutoGen, CrewAI, LlamaIndex).
• Proven experience designing and deploying RAG systems in production.
• Experience implementing MCP or similar protocol-based integrations.
• Experience working with vector databases and embedding models.
• Familiarity with cloud platforms (Azure, AWS, or GCP).
• Working knowledge of Docker and Kubernetes basics.
• Strong understanding of AI safety, governance, and data security principles.
• Excellent communication and stakeholder management skills.

Nice-to-Have Skills

• Experience with LangOps / MLOps practices, including evaluation frameworks.
• Knowledge of search systems (Elasticsearch/OpenSearch), OCR, and document processing pipelines.
• Experience with enterprise AI platforms such as OpenAI, Azure OpenAI, Claude, Gemini, and Llama models.
• Frontend integration experience for AI copilots or chat interfaces.
• Exposure to regulated industries (BFSI, Healthcare, etc.).

Soft Skills

• Strong documentation and communication skills.
• Ownership mindset with accountability for end-to-end delivery.
• Analytical and problem-solving orientation.
• Ability to collaborate effectively with cross-functional teams.

Education

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.