Software Engineering Intern

Software Engineering Intern - Unbound

The Problem

AI coding agents (Claude Code, Cursor, Copilot) can write code, run shell commands, and modify infrastructure across an entire engineering org. Most companies have zero visibility into what these agents are doing and no way to stop a bad tool call before it executes.

Were building the governance and security layer for AI coding agents: agent and tool discovery across dev fleets, usage and token analytics through an LLM gateway, and runtime policy enforcement that intercepts risky actions before they happen.

Who We Are

Were Vignesh and Raj. We come from deep engineering, product, and security backgrounds. We started Unbound because we kept seeing orgs hand AI agents broad access to codebases, infrastructure, and APIs with zero guardrails. That felt like a problem worth solving. Were YC-backed and building out of the Bay Area.

What Youll Do

Ship real features. Youll own features from design through deployment. Your code runs in production and gets used by engineering teams at real companies.

Work across the stack. Our product spans agent discovery, an LLM gateway, and a runtime policy engine. Youll touch Python, Ruby on Rails, Next.js, Kubernetes, and cloud infra. If you havent used something on this list, youll learn it here.

Work with founders directly. Youll have full context on what were building and why. Youll sit in on customer calls, see the roadmap, and understand the business, not just your tickets.

Pick up what matters. No backlog grooming ceremonies. Youll see gaps, flag them, and fill them.

Build in AI security. Youll work hands-on with how AI agents operate under the hood (hooks, MCP servers, tool-use lifecycles) and build the guardrails around them. This space barely existed a year ago.

Your First 30 Days

In your first two weeks, youll ship a feature to production. Past projects have included agent integrations, policy engine rules, and dashboard features. Your project depends on whats highest priority when you start, but it will be real and it will ship. By day 30, youll have full context on the product, customers, and codebase, and youll be picking up work on your own.

What Were Looking For

• You can ship. Youve built and deployed something: a side project, a class project, a startup, open source. The bar isnt perfection, its follow-through.
• Youre comfortable with ambiguity. Well give you a problem, not a spec. You figure out the approach, ask good questions, and iterate.
• You code with AI tools and stay in control. We expect you to use Copilot, Claude, whatever works. But you understand what the code does and can debug it when it breaks.
• Youre curious about security, devtools, or infrastructure. Deep experience not required, but genuine interest matters. If youve thought about what happens when an AI agent has root access to a codebase, we should talk.
• You want to understand how the whole system works, not just your piece of it.
  
  

• Experience with Python, TypeScript/Next.js, or Ruby on Rails
• Familiarity with cloud infrastructure (Azure, AWS, K8s)
• Experience building in the AI/LLM stack
• Youve been a founder or want to be one
  
  

• Ruby on Rails
• Next.js
• Azure
• Kubernetes
• OpenAI
• Anthropic
• Google Vertex AI
  
  

• Small team, high trust. No micromanagement. We trust you to manage your time and deliver.
• Async-first. We dont burn your day with meetings. Communication happens in writing, calls happen when they need to.
• Direct feedback. We tell you whats working and what isnt. We expect the same back.
• Ship > talk about shipping. Wed rather see a rough working prototype than a polished slide deck.