Data Scientist (on Gen AI / Agentic AI Lead)

Qualifications

• Infosys is seeking a hands-on Gen AI / Agentic AI Lead to drive the development and deployment of next-generation AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI frameworks
• This role is ideal for a mid-level engineer with strong technical depth, a passion for building, and the ability to lead small teams or workstreams in a fast-paced, innovation-driven environment
• Bachelor’s degree in Computer Science, AI/ML, or related field
• 5–8 years of experience in software engineering or data science, with 2–3 years in Gen AI or LLM-based systems
• Strong Python programming skills and experience with ML/AI libraries (Hugging Face Transformers, LangChain, PyTorch)
• Hands-on experience with vector databases (FAISS, Pinecone, Weaviate, Azure AI Search)
• Familiarity with cloud platforms and Gen AI services (AWS, Azure, Google Cloud Platform)
• Experience with REST API development (FastAPI, Flask) and containerization (Docker)
• Solid understanding of AI governance, model safety, and prompt engineering

Responsibilities

• Design, develop, and deploy Gen AI applications using LLMs and agentic frameworks (e.g., LangGraph, AutoGen, Crew AI)
• Fine-tune open-source and proprietary LLMs using techniques like LoRA, QLoRA, and PEFT
• Build and optimize RAG pipelines with hybrid retrieval, semantic chunking, and vector search
• Integrate Gen AI solutions with cloud-native services (AWS Bedrock, Azure OpenAI, Google Cloud Platform Vertex AI)
• Work with unstructured data (PDFs, HTML, audio, images) and multimodal models
• Implement LLMOps practices including prompt versioning, caching, observability, and cost tracking
• Evaluate model performance using tools like RAGAS, DeepEval, and FMeval
• Collaborate with product managers, data engineers, and UX teams to deliver production-ready solutions
• Mentor junior engineers and contribute to code reviews, design discussions, and best practices

Full Description

Role: Data Scientist (on Gen AI / Agentic AI Lead)

Location: - Alpharetta, GA Bridgewater, NJ

Charlotte, NC

Denver, CO

Hartford, CT

Houston, TX

New York, NY

Palm Beach, FL

Phoenix, AZ

Raleigh, NC

Richardson, TX

Sunnyvale, CA

Tampa, FL

Tempe, AZ

Washington, VA

Preferred Qualifications

Infosys is seeking a hands-on Gen AI / Agentic AI Lead to drive the development and deployment of next-generation AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI frameworks.

This role is ideal for a mid-level engineer with strong technical depth, a passion for building, and the ability to lead small teams or workstreams in a fast-paced, innovation-driven environment.

Required Qualifications

• Bachelor’s degree in Computer Science, AI/ML, or related field.

• 5–8 years of experience in software engineering or data science, with 2–3 years in Gen AI or LLM-based systems.

• Strong Python programming skills and experience with ML/AI libraries (Hugging Face Transformers, LangChain, PyTorch).

• Hands-on experience with vector databases (FAISS, Pinecone, Weaviate, Azure AI Search).

• Familiarity with cloud platforms and Gen AI services (AWS, Azure, Google Cloud Platform).

• Experience with REST API development (FastAPI, Flask) and containerization (Docker).

• Solid understanding of AI governance, model safety, and prompt engineering.

Key Responsibilities

• Design, develop, and deploy Gen AI applications using LLMs and agentic frameworks (e.g., LangGraph, AutoGen, Crew AI).

• Fine-tune open-source and proprietary LLMs using techniques like LoRA, QLoRA, and PEFT.

• Build and optimize RAG pipelines with hybrid retrieval, semantic chunking, and vector search.

• Integrate Gen AI solutions with cloud-native services (AWS Bedrock, Azure OpenAI, Google Cloud Platform Vertex AI).

• Work with unstructured data (PDFs, HTML, audio, images) and multimodal models.

• Implement LLMOps practices including prompt versioning, caching, observability, and cost tracking.

• Evaluate model performance using tools like RAGAS, DeepEval, and FMeval.

• Collaborate with product managers, data engineers, and UX teams to deliver production-ready solutions.

• Mentor junior engineers and contribute to code reviews, design discussions, and best practices.

Preferred Data Scientist Qualifications:

• Exposure to agentic workflows and autonomous agents.

• Experience with CI/CD pipelines and DevOps tools (GitHub Actions, Jenkins, Terraform).

• Familiarity with front-end integration (React, Angular, TypeScript) and GraphQL APIs.

• Knowledge of model interpretability, bias mitigation, and human-in-the-loop systems.

• Experience with multimodal models and perception systems (e.g., vision + language).