Job description
This role is for one of the Weekday's clients Salary range: Rs 1800000 - Rs 3000000 (ie INR 18-30 LPA) Min Experience: 2 years Location: Bangalore JobType: full-time We are seeking a highly motivated AI Engineer with 2–6 years of experience to join a growing team working at the forefront of applied AI.
In this role, you will design and build intelligent systems powered by Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG).
You will play a key role in developing scalable, production-grade AI solutions that enhance knowledge discovery, automation, and decision-making across various domains.
Key Responsibilities: Design, develop, and deploy applications leveraging Large Language Models (LLMs), including both proprietary and open-source models Build and optimize Retrieval-Augmented Generation (RAG) pipelines for accurate, context-aware responses Implement document ingestion, embedding generation, vector search, and ranking systems using modern vector databases Fine-tune and evaluate LLMs for domain-specific use cases, improving performance, accuracy, and relevance Collaborate with cross-functional teams including product, data engineering, and backend teams to integrate AI solutions into production systems Develop prompt engineering strategies and experiment with chaining techniques to enhance model outputs Ensure scalability, reliability, and cost-efficiency of deployed AI systems Stay updated with the latest advancements in generative AI, LLM architectures, and retrieval techniques Required Skills & Qualifications: 2–6 years of hands-on experience in AI/ML, with a strong focus on NLP and generative AI Solid understanding of Large Language Models (LLMs), transformers, and their real-world applications Proven experience in building RAG-based systems, including knowledge retrieval, embeddings, and vector databases (e.
g., FAISS, Pinecone, Weaviate) Proficiency in Python and experience with ML frameworks such as PyTorch, TensorFlow, or Hugging Face Transformers Experience with prompt engineering, model evaluation, and performance optimization techniques Familiarity with APIs and deployment frameworks such as FastAPI, Docker, or cloud platforms (AWS, GCP, Azure) Strong problem-solving skills and the ability to translate business requirements into technical solutions Preferred Qualifications: Experience with LLM orchestration frameworks such as LangChain or LlamaIndex Understanding of data pipelines, ETL processes, and handling large-scale unstructured data Exposure to fine-tuning techniques such as LoRA, PEFT, or instruction tuning Knowledge of search systems, semantic search, and hybrid retrieval methods Prior experience deploying AI systems in production environments
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