AI Engineer

Location : Role is remote, however you must be based within a City location in India

Our client who provides world’s leading Agent and Agentic solution platform designed for teams looking to streamline operational efficiency and scale productivity without needing to add headcount is currently hiring for an AI Engineer.

What You'll Do

AI / ML Engineering

Build and deploy production-grade AI / ML features using LLM APIs (OpenAI, Anthropic, etc.) and agent orchestration frameworks

Design, implement, and optimize RAG pipelines including embedding strategies, vector search, and retrieval patterns

Develop multi-agent systems with tool use, memory management, and planning capabilities using frameworks like Mastra, LangChain, or LlamaIndex

Engineer and iterate on prompts to optimize LLM performance, accuracy, and cost-efficiency

Backend Development

Build and deploy high-quality features using TypeScript (70%) and Python (30%) for AI / ML workloads

Design and maintain relational databases (Azure SQL) and vector databases, ensuring optimal performance and data integrity

Develop and integrate clean, scalable APIs to support AI-powered features and 3rd-party services

Collaboration & Ownership

Collaborate with product team to deliver AI / ML capabilities that solve real user problems

Take full ownership of feataures from concept to production deployment

Contribute to engineering best practices and participate in code reviews with a constructive mindset

Required :

5+ years of backend development experience in a commercial setting

2+ years of production experience building and deploying LLM-based applications

Strong understanding of RAG concepts : embeddings, vector search, retrieval strategies, and chunking approaches

Hands-on experience with an agent orchestration framework (Mastra, LangChain, LlamaIndex, or similar)

Experience building multi-agent systems with tool use, memory, and planning capabilities

Proficiency in TypeScript (primary) and Python, ideally with knowledge of NodeJS

Solid experience with relational databases and familiarity with vector databases

Experience working in cloud environments (preferably Azure, with exposure to Kubernetes, Docker, etc.)

Comfortable with version control and collaboration tools like GitHub

A hands-on "doer" who executes efficiently and takes pride in shipping quality code

Excellent communication skills and fluency in English