AI Product Engineer – Dashboard Creation & n8n Automation

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.

What You Will Build & Own

• 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.

Who We're Looking For

• 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 — the problem it solves, the architecture, technologies used, key challenges, and what you'd improve. A GitHub repo, deployed app, or working demo is strongly preferred; copied tutorial or academic-only projects won't count. Hackathons, competitions, and open-source work are a strong plus.

Strongly Preferred

LLM APIs (OpenAI, Gemini, Groq); RAG, vector databases, embeddings, LangChain / LangGraph, or AI-agent development; FastAPI, Flask, Django, Streamlit, or React; cloud deployment, Docker, authentication, and production API integrations; automation / workflow orchestration and CRM / LMS / HR integrations; and experience building products used by real users.

What We Offer

• Real ownership: your work ships into products and systems used across the organization.

• Production exposure: build, deploy, debug, and improve real applications.

• AI exposure: work with modern LLMs, RAG, AI agents, and automation.

• Growth through responsibility: scope grows as your ability to own projects grows