Full Stack AI Engineer

About the Role

Help build the AI solutions that will redefine how marketing gets done. We are building the next generation of AI and GenAI products. This is a hands-on role at the intersection of AI engineering and full stack development — where ideas move from concept to production and actually ship. We are looking for a builder who has done it before, not just prototyped it.

Key Responsibilities

• Own solutions end to end: Build and deploy production grade AI and GenAI solutions, from backend to frontend.
• Build agentic systems: Design and implement Agentic AI workflows using frameworks like LangChain or LangGraph, including multi-agent systems, MCP, and tool calling.
• Build the intelligence layer: Implement RAG pipelines, work with vector databases, and integrate LLMs into real products.
• Own the full stack: Develop robust backends in Python and FastAPI and intuitive frontends in React or similar frameworks.
• Ship on cloud: Deploy and scale on AWS, Azure, or GCP using Docker, Kubernetes, and CI/CD.
• Integrate and operationalize: Build API integrations and data pipelines that connect AI systems to business systems.
• Work with business and clients: Understand requirements from business and client teams and convert them into practical, scalable AI solutions.

Requirements & Tech Stack

• A proven builder: you have built and deployed AI and GenAI solutions in production, not just POCs.
• Full stack capable: strong experience in Python and FastAPI along with React or a similar frontend framework.
• AI engineering depth: hands-on experience with Agentic AI, LangChain, LangGraph, multi-agent systems, MCP and tool calling, RAG, and vector databases.
• Cloud native: experience with cloud platforms like AWS, Azure, or GCP, Docker, Kubernetes, and CI/CD.
• Product minded: experience with API integrations, data pipelines, and taking products from zero to one.
• Client facing: able to work with business and client teams, translate ambiguous requirements into working solutions.
• Curious and pragmatic: you stay close to what is new but care most about what works in production.

Location: Bangalore (Full-time)