Software Engineering / Data Science Intern

What You'll Do

• Take product requirements or a PM-built POC and engineer a scalable, production-quality MVP
• Build and iterate on user-facing interfaces: web apps, dashboards, internal tools — using AI-assisted coding tools throughout
• Develop and optimize data pipelines, ETL processes, and integrations on Databricks using dbt and PySpark
• Build and refine AI agents to automate complex operational workflows
• Work closely with data engineers and analysts to ensure data quality, pipeline reliability, and model integration
• Collect rapid user feedback, iterate on UX, and push features through testing to production
• Document technical architecture, APIs, and data flows for handoff to full-time engineering
• Participate in code reviews, sprint planning, and agile ceremonies

Tech Stack

• Data & Pipelines: Databricks, PySpark, dbt, Azure Data Factory, SQL
• AI/ML: Python, LLM APIs (Anthropic, OpenAI), prompt engineering, agent frameworks
• Frontend/Internal Tools: React, Streamlit, Retool, v0, or equivalent
• Dev Tools: GitHub, Azure DevOps, Jira, Claude Code, Cursor

Must Have

• Currently pursuing a Bachelors (or Masters) degree in Computer Science, Software Engineering, AI/ML, Data Science, or equivalent technical field
• Demonstrated technical portfolio: GitHub repos with meaningful commits, a deployed project, hackathon work, or open-source contributions
• Strong Python skills; experience with SQL and data manipulation
• Experience building and deploying something end-to-end — not just tutorials
• Fluency with AI coding tools (Claude Code, Copilot, Cursor) as a core part of your workflow
• Able to debug independently and ship fast under ambiguity

PREFERRED

• Hands-on experience building LLM-powered applications or AI agents
• Frontend development experience (React, TypeScript, or rapid prototyping tools)
• Exposure to cloud platforms (Azure, AWS, or GCP)
• Prior internship or project experience in fintech, banking, or enterprise software