Data Scientist with Gen ai

2 days ago

Bengaluru, Karnataka, India People Prime Worldwide Full time ₹ 9,00,000 - ₹ 12,00,000 per year

Our is Client is a largest Top 5 Software giant in India, with over 11.3 USD billion dollars revenue, Global work force 2,40,000 employees, It delivers end-to-end technology, consulting, and business process services to clients across the globe, Presence: 60+ countries and Publicly traded company NSE & BSE (India), NYSE (USA).

· Job Title: Data Scientist With Gen AI

· Location: Bengaluru, Chennai

· Experience: 5+ years

. Interview Mode: Face to Face (F2F)

. Date And Time: Saturday)

· Job Type : Full Time Permanent

· Notice Period:- Immediate joiners

. Client : MNC Client

Data Scientist: 5-10 years

  • 5+ years of work experience with a bachelor's degree or an advanced degree in Computer Science, Information Technology, Engineering, or a related field.
  • 3+ Experience with building backend services and APIs, including integration with distributed data systems and cloud-native architectures.
  • 3+ Strong experience in writing efficient, maintainable code for large-scale systems and data-driven applications.
  • 1+ years of hands-on experience with GenAI technologies — including LLMs, promptengineering, embeddings, fine-tuning, or building RAG (Retrieval-Augmented Generation) pipelines.
  • Strong programming skills in one or more languages such as Python, Java, or Scala, with a solid foundation in software design principles, testing, and version control (e.g., Git). Python developers are preferred.
  • Strong backend engineering background with expertise in building scalable systems using Python, C#, Java or similar, and hands-on experience with microservices, REST APIs, Kafka, and cloud platforms (AWS/Azure) — preferably with exposure to secure, low-latency architectures.
  • Demonstrated interest or experience in GenAI/Agentic AI systems — including building or integrating with LLMs (e.g., OpenAI, Claude), use of tools like LangChain, LangGraph, Copilot, or vector DBs, or implementing AI agent orchestration logic in real-world workflows.
  • Comfortable working in AI-first environments, with experience using modern developer tools (e.g., Docker, Kubernetes, CI/CD, Git), and exposure to prompt engineering, embeddings, or AI-based toolchains preferred.

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