AI Engineer (LLMs & Generative AI)

Overview

1–2 Years (Full-Time)

Location: Gurgaon (Work From Office – 5 Days a Week)

Overview

We are seeking a motivated AI Engineer with 1–2 years of hands-on experience in building and deploying LLM-powered applications. The role involves working on model fine-tuning, Retrieval-Augmented Generation (RAG) systems, and AI agent frameworks to build scalable, real-world AI products. You’ll collaborate closely with engineering and product teams and contribute across experimentation, development, and optimization.

Key Responsibilities

• Design, build, and optimize LLM-based applications using frameworks such as Hugging Face, OpenAI APIs, LangChain, or similar.
• Develop and maintain RAG pipelines, including embeddings generation, vector databases, retrieval strategies, and prompt orchestration.
• Fine-tune and adapt language models for specific use cases, balancing performance, cost, and latency.
• Implement model evaluation, monitoring, and optimization using well-defined quality and performance metrics.
• Build and experiment with AI agent frameworks (e.g., LangGraph, CrewAI, AutoGen, AgentKit) for multi-step reasoning and workflows.
• Collaborate with cross-functional teams to translate product requirements into AI solutions.
• Stay up to date with the latest advancements in LLMs, GenAI tooling, and best practices, and apply them to ongoing projects.
  
  

• Strong foundation in Machine Learning, NLP, and Python programming.
• Practical experience with PyTorch, Hugging Face Transformers, and modern LLM workflows.
• Hands-on experience building applications using OpenAI or similar LLM platforms.
• Experience working with LangChain (or equivalent frameworks) and vector databases (e.g., FAISS, Pinecone, Weaviate, Chroma).
• Ability to take ML/AI projects from experimentation to production-ready prototypes.
• 1–2 years of professional or equivalent hands-on experience, including strong personal or open-source projects in NLP/LLMs.
  
  

• Exposure to deployment workflows (APIs, Docker, cloud platforms).
• Experience with prompt engineering, evaluation frameworks, or observability tools for LLMs.
• Familiarity with cost optimization and latency tuning for LLM-based systems.
  
  

You are curious, proactive, and passionate about generative AI. You enjoy experimenting, learning quickly, and building practical solutions with LLMs. You’re comfortable taking ownership of features and thrive in a fast-paced environment focused on real-world AI products.