Generative AI Engineer

Job Title: Generative AI Engineer LLM & RAG

Experience: 6–9 Years
Locations: Pune, Chennai, Bangalore

Job Overview

We are looking for an experienced Generative AI Engineer with hands-on expertise in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI application development. The ideal candidate should have strong Python programming skills and experience building, integrating, and deploying production-ready Generative AI solutions.

Key Responsibilities

• Design, develop, and deploy Generative AI applications using Large Language Models (LLMs).
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines for enterprise use cases.
• Integrate LLMs with enterprise data sources, APIs, and knowledge bases.
• Implement document ingestion, chunking, embedding generation, semantic search, and retrieval workflows.
• Work with vector databases such as FAISS, Pinecone, Chroma, or Azure AI Search.
• Develop AI applications using frameworks such as LangChain or LlamaIndex.
• Integrate commercial or open-source LLMs, such as OpenAI GPT models, Anthropic Claude, or Llama.
• Improve response quality through prompt engineering, retrieval tuning, evaluation, and hallucination reduction.
• Develop APIs and backend services using Python frameworks such as FastAPI.
• Implement testing, monitoring, security, and performance optimization for AI applications.
• Collaborate with data engineering, cloud, product, and business teams to deliver scalable AI solutions.

Mandatory Skills

• Strong Python programming and software development fundamentals.
• Hands-on experience with Generative AI and LLM-based applications.
• Practical experience designing and implementing RAG architectures.
• Knowledge of embeddings, vector search, semantic retrieval, and prompt engineering.
• Experience with LangChain, LlamaIndex, or equivalent frameworks.
• Understanding of LLM evaluation, response quality, and hallucination mitigation.
• Experience integrating AI applications with APIs and enterprise data sources.

Good-to-Have Skills

• Experience with vector databases such as Pinecone, FAISS, Chroma, or Weaviate.
• Knowledge of cloud AI platforms such as AWS Bedrock, Azure OpenAI, or Google Vertex AI.
• Experience with LLM agents, tool calling, and multi-step workflows.
• Familiarity with Docker, Kubernetes, CI/CD, and production deployment.
• Knowledge of model fine-tuning, observability, and responsible AI practices.

Experience Requirements

• 6–9 years of overall software development or relevant engineering experience.
• Hands-on project experience delivering LLM and RAG-based applications.
• Strong problem-solving, analytical, and communication skills.

Preferred Candidate Profile

Candidates should have practical experience building production-grade Generative AI solutions, particularly RAG applications, rather than only theoretical knowledge of LLMs or prompt engineering.