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.
Requirements
- 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, GCP).
- Experience with REST API development (FastAPI, Flask) and containerization (Docker).
- Solid understanding of AI governance, model safety, and prompt engineering.
- Exposure to agentic workflows and autonomous agents.
- Experience with CI/CD pipelines and DevOps tools (GitHub Actions, Jenkins, Terraform).
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, GCP 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.
Other
- 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.
- This position is based out of Raleigh, NC / Richardson, TX / Tempe, AZ / Phoenix, AZ / Charlotte, NC / Houston, TX /Alpharetta, GA / Palm Beach , FL / Sunnyvale, CA and may require to travel.
- 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.
