AI Integration & Data Engineer Internship - Vosyn

About Us:

At Vosyn , we embrace the exciting, game-changing world of Artificial Intelligence, driving innovation and pioneering impactful projects across various industries. We are a trailblazing Language Synthesis AI firm reshaping global communication by dissolving language barriers and empowering users. We believe in fostering a culture of flexibility, continuous improvement, and solution-focused strategies. Here, every idea is welcomed, nurtured, and has the potential to scale to new heights. Currently, we're at the forefront of a significant IPO endeavor, truly aunicorn in the making. We invite you to be part of our journey and leave your imprint on the future of AI.

About the Role:

We are seeking a capable, detail-driven AI Integration & Data Engineer Intern to own the connective tissue of every project: the data plumbing and the integrations into the systems a client already runs. This role is ideal for a Master’s level student who uses AI coding tools to move fast but has the engineering depth to handle the part those tools are worst at bespoke integration with messy, real-world data. You will connect to client databases, APIs, and SaaS systems; extract, clean, transform, and move data so it is usable by AI features; and build the pipelines that feed the agents and retrieval systems your teammates create. More than half the real work of any AI project lives here, and it is the difference between a demo and something that runs in production.

Tools & Tech Stack:

• AI-native IDEs / editors: Cursor, Windsurf, GitHub Copilot; agentic CLI coders (Claude Code, Aider)

• Back-end: Node.js and/or Python

• Databases & BaaS: PostgreSQL, Supabase, Firebase; familiarity with SQL
• Data movement: APIs and webhooks, ETL/data pipelines, data cleaning and transformation
• Integration & automation glue: MCP (Model Context Protocol), Zapier, Make, or n8n where useful
• Version control & documentation: Git / GitHub, Notion

Key Responsibilities:

• Connect to client systems — databases, APIs, CRMs, and other SaaS tools — and get data reliably out of and into them.
• Extract, clean, transform, and move data so it is structured and usable by AI features, including retrieval and agentic workflows.
• Build and maintain data pipelines that feed the Applied AI Engineer’s RAG and agent systems with current, correct data.
• Use AI coding tools to accelerate integration work, while applying real engineering judgment to the bespoke, messy parts those tools handle poorly.
• Handle the practical realities of client data: undocumented schemas, inconsistent formats, partial records, and access constraints.
• Apply data-handling, security, and privacy best practices throughout, especially with client data.
• Collaborate with the Builder and the Applied AI Enginee