Infosys
Infosys

Technology Architect - AI/GenAI-Q2 FY 27

职能机器学习
级别中级
地点Bangalore, India
方式现场办公
类型Technology Architect
发布2个月前
立即申请

职位介绍

We are looking for a highly skilled Generative AI Engineer / Senior Technologist with strong hands-on experience in Python, Large Language Models, RAG, Agentic AI, fine-tuning, and cloud deployment. The ideal candidate should have a deep understanding of LLM architectures at a systems level and the ability to design, build, deploy, and evaluate end-to-end AI solutions for enterprise use cases.
This role requires strong engineering capability, problem-solving skills, and practical exposure to modern AI frameworks, cloud-native deployment, and model engineering concepts.

  • 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, Lang Chain, Lang Graph, Llama Index, Auto Gen, 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.
    • Education: Bachelor of Engineering

Preferred skills: Technology->AI-Responsible AI->Responsible AI->explainable ai,Technology->AI-AI Engineering->LLMOps

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