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Generative AI Engineer - LLM

Generative AI Engineer - LLM

Randstad DigitalGurgaon
30+ days ago
Job description

Job Title : LLM Engineer

Experience : 5+ Years (Relevant : 46 Years)

Location : Gurgaon

Looking for Immediate Joiners only.

About the Role :

We are seeking a highly skilled and experienced LLM Engineer to join our cutting-edge GenAI team. The ideal candidate will have a strong background in Python, Prompt Engineering, Agentic AI, and frameworks like LangGraph. You will play a key role in developing, deploying, and optimizing Large Language Model (LLM)-based applications, agents, and pipelines to solve real-world problems and drive innovation in intelligent systems.

Key Responsibilities :

  • Design, build, and deploy scalable applications using Large Language Models (LLMs).
  • Develop intelligent agents using LangGraph and other agentic AI techniques.
  • Create and optimize prompts to improve LLM task performance across multiple domains.
  • Collaborate with cross-functional teams including data scientists, ML engineers, and product managers to integrate GenAI solutions into products.
  • Fine-tune and evaluate LLMs for domain-specific tasks and use cases.
  • Contribute to building internal tools, libraries, and reusable components for GenAI development.
  • Monitor, evaluate, and continuously improve system performance, accuracy, and safety.

Required Skills & Experience :

  • 46 years of hands-on experience in building and deploying GenAI / LLM-based solutions.
  • Strong proficiency in Python and associated libraries for NLP and LLMs (e.g., LangChain, Transformers, LangGraph).
  • Deep understanding of Prompt Engineering and its application in production systems.
  • Experience building Agentic AI systems and workflow-driven intelligent applications.
  • Solid understanding of LLMs (e.g., GPT, LLaMA, Claude) and their Familiarity with model evaluation metrics and ethical considerations around LLM use.
  • Strong problem-solving skills, communication, and the ability to work in an agile environment.
  • Preferred Qualifications :

  • Experience working with vector databases (e.g., FAISS, Pinecone).
  • Exposure to knowledge retrieval (RAG), few-shot learning, or fine-tuning.
  • Contributions to open-source GenAI projects or frameworks.
  • Experience deploying LLMs at scale on cloud platforms (AWS, GCP, Azure).
  • (ref : hirist.tech)

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