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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
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