
Generative AI Engineer
4 weeks ago
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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