AI Engineer - LLMs / Generative AI / AI Agents

The Car Site Limited; Bengaluru; On-site; INR 2,200,000 - 4,200,000; Full time

Job summary

The Car Site Limited is seeking an AI Engineer to design, develop, and deploy AI-powered applications using LLMs and Generative AI. You will build intelligent agents, enable multi‑step task execution, and integrate AI with external systems to automate real-world workflows.

You will collaborate with backend/frontend teams and leadership to move AI solutions from experimentation to production, owning critical components of the AI stack and contributing to architecture decisions.

Qualifications

• 4+ years of software engineering experience with hands‑on AI/ML or Generative AI.
• Strong programming experience in Python.
• Practical experience with LLM APIs such as OpenAI, Anthropic or Google Gemini.
• Experience building apps using LLMs and Generative AI.
• Experience with prompt engineering, context management and token optimization.
• Hands‑on experience with RAG architectures and vector databases.
• Familiarity with embeddings, semantic search and information retrieval.
• Experience building REST APIs and integrating external services.
• Knowledge of asynchronous programming and event‑driven architectures.

Responsibilities

• Design, develop and deploy AI-powered applications using LLMs and Generative AI.
• Build intelligent AI agents capable of executing multi-step tasks and interacting with external systems.
• Develop conversational AI solutions with context awareness and memory.
• Design and implement Retrieval-Augmented Generation pipelines.
• Integrate LLMs with external APIs, databases and third-party services.
• Build agentic workflows using tool calling and orchestration frameworks.
• Process, analyse and extract insights from unstructured data.
• Implement prompt engineering and optimize model performance.
• Evaluate outputs for accuracy, latency and cost; implement guardrails and fallbacks.
• Develop scalable APIs and services to integrate AI with existing apps.
• Monitor and improve AI applications in production; stay updated with AI advances.

Skills

Python

LLMs

OpenAI API

RAG

Vector DB

REST APIs

Asynchronous

Testing & Debugging

Problem Solving

Communication

Tools

LangChain

LangGraph

LlamaIndex

Pinecone

Qdrant

Weaviate

pgvector

Docker

AWS

Node.js

TypeScript

PostgreSQL

Job description

We are looking for an AI Engineer with hands‑on experience in building and deploying AI‑powered applications using Large Language Models (LLMs), Generative AI and modern AI frameworks.

You will be responsible for designing, developing and integrating intelligent systems that solve real‑world business problems through automation, conversational interfaces and AI‑driven workflows.

You will work closely with backend engineers, frontend engineers, product stakeholders and engineering leadership to take AI solutions from experimentation to production.

This is a hands‑on engineering role offering significant ownership and the opportunity to work with emerging AI technologies in a growing product‑focused organisation.

Key Responsibilities

• Design, develop and deploy AI‑powered applications using LLMs and Generative AI technologies.
• Build intelligent AI agents capable of executing multi‑step tasks and interacting with external systems.
• Develop conversational AI solutions with context awareness, memory and natural language understanding.
• Design and implement Retrieval‑Augmented Generation (RAG) pipelines.
• Integrate LLMs with external APIs, databases and third‑party services.
• Build agentic workflows using tool calling, function calling and orchestration frameworks.
• Develop systems for processing, analysing and extracting insights from unstructured data.
• Implement prompt engineering techniques and optimise model performance.
• Evaluate AI outputs for accuracy, reliability, latency and cost.
• Implement appropriate guardrails, error handling and fallback mechanisms.
• Develop scalable APIs and services to integrate AI capabilities with existing applications.
• Monitor, troubleshoot and continuously improve AI applications in production.
• Stay up to date with emerging developments in LLMs, AI frameworks and agentic architectures.

Required Skills & Experience

• 4+ years of software engineering experience, with meaningful hands‑on experience in AI/ML or Generative AI.
• Strong programming experience in Python.
• Practical experience working with LLM APIs such as OpenAI, Anthropic or Google Gemini.
• Experience building applications using LLMs and Generative AI.
• Understanding of prompt engineering, context management and token optimisation.
• Hands‑on experience with RAG architectures and vector databases.
• Understanding of embeddings, semantic search and information retrieval.
• Experience building REST APIs and integrating external services.
• Familiarity with asynchronous programming and event‑driven architectures.
• Good understanding of software engineering principles, debugging and testing.
• Experience taking applications from development to production.

Good to Have

• Experience with AI agent frameworks such as LangChain, LangGraph, LlamaIndex or similar.
• Experience implementing MCP (Model Context Protocol) servers and clients.
• Familiarity with multi‑agent architectures and agent orchestration.
• Experience with vector databases such as Pinecone, Qdrant, Weaviate or pgvector.
• Working knowledge of Node.js and TypeScript.
• Familiarity with PostgreSQL and relational database concepts.
• Experience with speech‑to‑text, text‑to‑speech and audio processing technologies.
• Experience with conversational AI platforms and chatbot development.
• Familiarity with Docker, AWS and cloud‑based deployments.
• Experience with LLM evaluation frameworks, observability and monitoring.
• Exposure to open‑source models and frameworks such as Hugging Face.

What We're Looking For

• Strong problem‑solving and analytical abilities.
• A practical engineering mindset with a focus on building working solutions.
• Ability to distinguish between problems that require AI and those better solved using conventional software engineering.
• Comfortable experimenting with new technologies and translating prototypes into production‑ready systems.
• Ability to work independently and take end‑to‑end ownership.
• Strong understanding of system design, scalability and reliability.
• Ability to balance AI model quality, application performance and infrastructure costs.
• Good communication and collaboration skills.
• Comfortable working in a fast‑moving product engineering environment.

What We Offer

• Opportunity to build and deploy real‑world AI‑powered products.
• Hands‑on exposure to LLMs, Generative AI and agentic architectures.
• Opportunity to experiment with emerging AI technologies and frameworks.
• A small, collaborative engineering team with significant ownership.
• Direct collaboration with engineering leadership and product stakeholders.
• Opportunity to influence technical architecture and engineering decisions.