# AI Engineer - RAG & Large Language Models

**Company:** [Weekday AI](http://jobs.workable.com/companies/pxG9rDgnvZm2c86JUchT1j.md)
**Location:** Bengaluru, India
**Workplace:** on site
**Employment type:** Full-time
**Department:** Weekday's Client via platform

[Apply for this job](http://jobs.workable.com/view/5e0e08de-9446-45f9-9042-561220fa2fd9)

## 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.

## Requirements

**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