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Gen AI / Agentic AI Lead

AT Infosys
Infosys

Gen AI / Agentic AI Lead

Alpharetta, GA

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, GCP).
  • Experience with REST API development (FastAPI, Flask) and containerization (Docker).
  • Solid understanding of AI governance, model safety, and prompt engineering.
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.

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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, 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.
  • 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).
The job entails sitting as well as working at a computer for extended periods of time. Should be able to communicate by telephone, email or face-to-face.

Estimated annual compensation range for candidates in the below locations will be-
Sunnyvale, CA: $73000 to $122275

Along with competitive pay, as a full-time Infosys employee, you are also eligible for the following benefits:-
Medical/Dental/Vision/Life Insurance
Long-term/Short-term Disability
Health and Dependent Care Reimbursement Accounts
Insurance (Accident, Critical Illness, Hospital Indemnity, Legal)
401(k) plan and contributions dependent on salary level
Paid holidays plus Paid Time Off.

Client-provided location(s): Alpharetta, GA, USA
Job ID: Infosys-136005BR
Employment Type: Full Time

Perks and Benefits

  • Health and Wellness

    • Health Insurance
    • Life Insurance
    • HSA
    • Short-Term Disability
  • Parental Benefits

    • Birth Parent or Maternity Leave
    • Non-Birth Parent or Paternity Leave
    • On-site/Nearby Childcare
  • Office Life and Perks

    • Commuter Benefits Program
  • Vacation and Time Off

    • Paid Vacation
    • Paid Holidays
    • Personal/Sick Days
    • Sabbatical
  • Financial and Retirement

    • 401(K)
    • Relocation Assistance
  • Professional Development

    • Learning and Development Stipend
  • Diversity and Inclusion

    • Employee Resource Groups (ERG)