AI Product Engineer

Role Overview

We want someone who builds, ships, owns, and solves — not someone whose strength is only coursework. You'll take an unclear business problem, figure out what to build, and turn it into a working product across AI, software engineering, automation, web products, APIs, and internal tools. You own outcomes end-to-end and learn what you need as you go.

Responsibilities

• Build AI-powered applications using LLMs, RAG, AI agents, intelligent search, document processing, and automation.
• Develop internal portals, dashboards, and business tools (HR/ATS, LMS, productivity apps).
• Design REST APIs and integrate third-party services, CRMs, and internal platforms.
• Replace manual, repetitive processes with reliable automation.
• Build and maintain frontend and backend features for internal and customer-facing products.
• Work with databases, cloud services, and production deployment environments.
• Debug, test, deploy, monitor, and continuously improve applications after launch.
• Turn stakeholder requirements into practical technical solutions.

Requirements

• Builder mindset: you build things outside tutorials and can show evidence of it.
• Ownership: you break down a requirement, make decisions, and drive it to completion.
• Execution over theory: strong fundamentals matter, but we care most about what you can ship.
• Problem solver & fast learner: you debug, research, and pick up unfamiliar frameworks or APIs when the problem needs them.
• Product thinking: you care whether it solves the business problem, not just whether the code runs.
• Strong fundamentals: practical experience in Python or another modern language; APIs, databases, Git, and debugging.
• Generative AI basics: hands-on with LLM-based apps; able to build and deploy a complete project, not just notebooks.
• Mandatory Project Showcase: A project is mandatory. Be ready to showcase at least one project you personally built and explain it end-to-end.

Skills

• Python
• LLMs
• RAG
• AI Agents
• REST APIs