Associate Software Engineer (New Grad)

About the Role

Engineering at Study.com is AI-native. Our engineers direct coding agents every day, inside an agent framework we built ourselves. We define what "done" means and hold the bar on quality, security, and architecture; the agents do the typing. You will join a cross-functional team and grow into the work alongside the engineers around you. You will take features from acceptance criteria to production. This is a role for learning the craft, with the support to do it well. Architecture, security, and system-wide decisions stay with the team while you build toward them.

This role is based in our Mountain View, CA office and is hybrid in office Mondays, Wednesdays, and Thursdays.

Key Responsibilities

• Build and ship features with AI coding agents (e.g., Claude Code) as your primary way of producing software.
• Work across our stack: Java and Spring services, MySQL, and TypeScript/React frontend.
• Write the tests and acceptance criteria that tell an agent when a feature is done.
• Work with your team to review and ship your code.
• Flag the skills and guardrails that fail you, and help make them better.
• Follow your features after release: watch the metrics, take the feedback, and learn from the trade-offs your team makes.

Your First 90 Days

• Days 1 to 30: Ship to production in your first week, with help close at hand. By the end of the month you have several features live and you know your way around the product and the codebase.
• Days 30 to 60: Take on larger features. Understand the metric each one is meant to move, ship it, and follow through on what the data says. Land your first improvement to a skill or guardrail the team uses.
• Days 60 to 90: Work on features with more ambiguity. Join the technical design discussions for your team's work and start contributing to them. Move faster on the paths you now know well.

What You'll Learn

In your first year you will get good at:

• Breaking a product problem into work an agent can execute well, and spotting when it has not.
• Reading a diff critically, and taking a review on your own work.
• Testing and observability practice on a system that real students depend on.
• Our stack, end to end, and where its load-bearing parts are.
• When to trust what an agent hands you, and when to go read the code yourself.

Requirements & Tech Stack

• Evidence that you build and ship software (e.g., internships, personal projects, open source, hackathon work).
• Hands-on experience using AI coding tools to build non-trivial functionality, and opinions about where they excel and where they still need a human.
• Working proficiency in at least one general-purpose language (Java or TypeScript preferred).
• Familiarity with how web applications fit together, front end through database.
• Solid fundamentals in data structures and algorithms.
• Clear written communication, for specifying intent precisely.

Qualifications

• A BS or MS in Computer Science or a related field, recently completed or expected before your start date.

Nice to Have

• A portfolio or GitHub that shows a pattern of finishing and shipping things, especially things built largely with agents.
• Experience with Java and Spring, React, SQL, or NoSQL databases.
• Experience writing prompts, skills, or evaluations that make LLM-based tools more reliable.
• A habit of finishing what you start, and of asking about the things that look wrong.