Job Title : AI Engineer (LLM & GenAI)

Level : Mid-Level (2 to 5 years experience)

Our client is looking for an ambitious AI Engineer with hands-on experience building, deploying, and evaluating LLM-powered applications to join our core product and engineering team in India.

Role Overview

As a AI Engineer, you will bridge the gap between AI prototyping and robust, production-grade software. You will be responsible for building end-to-end LLM features from prompt engineering and Retrieval-Augmented Generation (RAG) architecture to fine-tuning open-source models, latency optimization, and agentic workflows. You will work closely with cross-functional product managers, full-stack engineers, and backend teams to ship high-impact GenAI features directly to production.

Key Responsibilities

LLM Integration & Architecture : Design and build production-ready LLM applications using commercial APIs (OpenAI, Anthropic) and open-source foundation models (Llama, Mistral).
RAG & Search Systems :



Build and optimize end-to-end Retrieval-Augmented Generation pipelines using vector search engines (Pinecone, Qdrant, Weaviate, pgvector), chunking strategies, and hybrid search mechanics.
Agentic Workflows : Orchestrate multi-step AI agents, function calling, and tool-use frameworks (e.g., LangGraph, AutoGen, CrewAI) for complex, non-linear tasks.
Model Fine-Tuning : Apply PEFT/LoRA, fine-tuning, and quantization techniques to optimize open-source models for domain-specific production use cases.
Evaluation & Monitoring : Build evaluation frameworks (hallucination detection, cost tracking, accuracy, latency) using tools like Ragas or TruLens to ensure high-quality AI outputs.
Backend Integration : Wrap AI workflows into high-performance REST or gRPC APIs (FastAPI/Python) and deploy via Docker/Kubernetes in cloud environments & Requirements :

Must-Haves

Experience : 2 to 6 years of experience in software engineering, machine learning, or backend development, with at least 1 - 2 years

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