Senior Technologist - AI/GenAI-Q3 FY 26

Infosys Limited; Bengaluru; On-site; INR 3,000,000 - 5,200,000; Full time

Job summary

Infosys Limited in Bengaluru, India, seeks a Senior Technologist specializing in AI/GenAI with 9-14 years of experience. You will design enterprise-grade Generative AI solutions, harness LLMs, embeddings, and prompts, and implement RAG-based retrieval and generation pipelines.

The role involves deploying AI workloads on cloud platforms and containerizing apps with Docker and Kubernetes. You will collaborate on data ingestion, processing, retrieval, and evaluation while considering model tuning

Qualifications

• Design and develop enterprise-grade Generative AI solutions using Python and modern AI frameworks.
• Build AI applications using LLMs, embeddings, prompts, function calling, tool usage, and agentic AI patterns.
• Implement Retrieval-Augmented Generation (RAG) pipelines for enterprise data retrieval and generation use cases.

Responsibilities

• Design end-to-end AI solutions: data ingestion, processing, retrieval, generation, evaluation.
• Work with Agentic AI frameworks such as CrewAI, LangChain, LangGraph, LlamaIndex, AutoGen, Langfuse.
• Apply prompt engineering to improve LLM accuracy, reliability, and usability.
• Evaluate fine-tuning vs RAG based on business and technical requirements.
• Support LLM fine-tuning workflows including instruction tuning and supervised fine-tuning.

Skills

Unix/Linux

Generative AI

AI/ML Architecture

Explainable AI

Cloud AI platforms

Education

Bachelor of Engineering

Tools

Docker

Kubernetes

Azure

AWS

GCP

Job description

Job ID/Reference Code INFSYS-INDEED1-254850

Work Experience 9 - 14 Years

Job Title Senior Technologist - AI/GenAI-Q3 FY 26

Educational Requirements Bachelor of Engineering

Service Line Strategic Technology Group

Responsibilities

• Design and develop enterprise-grade Generative AI solutions using Python and modern AI frameworks.
• Build AI applications using LLMs, embeddings, prompts, function calling, tool usage, and agentic AI patterns.
• Implement Retrieval-Augmented Generation (RAG) pipelines for enterprise knowledge retrieval and generation use cases.
• Design end-to-end AI solutions covering:
  • Data ingestion
  • Data processing
  • Retrieval
  • Generation
  • Evaluation
• Work with Agentic AI frameworks such as CrewAI, LangChain, LangGraph, LlamaIndex, AutoGen, and Langfuse.
• Apply prompt engineering strategies to improve LLM accuracy, reliability, and usability.
• Evaluate the suitability of fine-tuning vs RAG based on business and technical requirements.
• Support LLM fine-tuning workflows including instruction tuning and supervised fine-tuning.
• Manage data preparation for fine-tuning, including train/validation splits, data quality checks, and contamination prevention.
• Deploy AI workloads on cloud platforms such as Azure, AWS, or GCP.
• Containerize AI applications using Docker and work with basic Kubernetes concepts.
• Apply model engineering best practices for scalable, reliable, and production-ready AI systems.

Preferred Skills:

• Technology->Programming Languages
• OS->Open Systems (Unix/Linux)
• Technology->AI-Generative AI->Artificial Intelligence - BASIC
• Technology->AI-AI Engineering->AI/ML Solution Architecture and Design->generative ai
• Technology->AI-Responsible AI->Responsible AI->explainable ai