About the Role :

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.

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 :

- 5 - 8 years of software engineering experience, with meaningful hands-on experience in AI/ML or Generative AI.
- 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.
- 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.

Good to Have :

- Experience taking applications from development to production.
- 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 :

- Prospect to build and deploy real-world AI-powered products.
- Hands-on exposure to LLMs, Generative AI and agentic architectures.
- Chance 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.

📌 TheCarSite - AI Engineer - LLM/Generative AI (India)
🏢 TheCarSite
📍 India