- Location
- Redwood City, CA, US
- Type
- Internship
- Department
- Engineering
- Seniority
- Internship
- Education
- Master
- Source
- Breezy HR
Description
This position will have the opportunity to work on impactful projects and gain practical experience in software development. Specifically, this role focuses on developer-productivity engineering — building the internal tools, automation, and AI agents that change how every Bear engineer ships software. The individual will collaborate with a team of experienced engineers, while utilizing cutting-edge AI coding agents to build reliable, scalable solutions in a monorepo system. This internship is designed for students who are passionate about software engineering and eager to understand the intersection of technical implementation, engineering-team impact, and measurable business value. Above all, we are looking for someone with genuine grit — who treats a stubborn bug or an ambiguous spec as a problem to be cracked, not avoided — and who works alongside AI coding agents by asking sharp, persistent questions until every requirement and edge case is crystal clear.
Key Duties/Responsibilities:
- Engineering-Productivity Software Development
- Contribute to the design, development, and testing of internal tools and services, with a specific focus on automation that improves how Bear engineers build software — bug-triage and routing agents, software development workflow, and the pipelines behind the engineering productivity dashboard.
- AI-Assisted Engineering: Utilize AI coding agents to accelerate development — probing them with follow-up questions until the design, trade-offs, and edge cases are crystal clear, rather than accepting a black-box answer — while ensuring the creation of reliable and robust software.
- Write clean, efficient, and well-documented code with configuration-driven (YAML) rules that engineers can tune safely.
- Systems Integration & Problem Solving
- Analyze technical challenges and propose creative solutions that integrate Jira, Slack, GitHub, and internal identity/HR data sources.
- Adopt the engineer's-eye (end-user) perspective so that every tool provides tangible value and a seamless experience for the teams that depend on it.
- Reconcile inconsistent cross-system data and design for correctness with tests, fail-safe behavior, and coverage metrics that reveal silent misses.
- Show relentless follow-through on hard problems — keep digging through failing tests, confusing errors, and dead ends until the root cause is found and the problem is genuinely solved.
- Demonstrate flexibility by actively seeking feedback from stakeholders and adapting project direction to maximize impact.
- Collaboration & Growth
- Work closely with team members and cross-functional teams to execute projects, contributing directly to the monorepo (Bazel-based).
- Embrace a learning mindset and actively seek opportunities to expand your technical skills, particularly in AI-assisted development workflows.
- Participate in code reviews to ensure code quality and collaborate with team members to overcome obstacles.
- Documentation
- Create and maintain technical documentation, including design proposals, implementation notes, operations runbooks, and user guides that let the next person run and fix what you built.
- Create and maintain technical documentation, including design proposals, implementation notes, operations runbooks, and user guides that let the next person run and fix what you built.
Supervisory Responsibilities:
- None.
Required Skills/Abilities/Qualifications:
- Grit & Persistence: A never-give-up approach to hard problems — you stay with a stubborn bug or a murky requirement, work the problem from multiple angles, and see it through to a real solution instead of a workaround.
- Inquisitiveness with AI Agents: Skill at working with AI coding agents — asking sharp, persistent follow-up questions until the requirements, design, and rationale are crystal clear, and never shipping something you can't explain.
- AI Engineering Proficiency: Demonstrated ability to build reliable software using AI coding agents.
- Technical Fundamentals: Strong programming skills in one or more languages such as Python, Go, TypeScript, C++, or others (Python proficiency preferred for this role), and an understanding of computer science fundamentals, data structures, and algorithms.
- Correctness Mindset: Attention to edge cases and failure modes, and the habit of writing tests you actually rely on.
- Communication: Clear written communication — able to turn an ambiguous problem into a short design doc and explain a trade-off in plain language.
- Soft Skills: Excellent communication and collaboration skills, with the ability to work effectively in a team setting.
Preferred Skills/Abilities (Big Plus):
- System Integration: Prior experience integrating systems with third-party APIs (Slack, GitHub, Jira, or similar) or building small automation/bots.
- CI/CD & Build Systems: Familiarity with CI/CD, GitHub Actions, or build systems (Bazel a plus).
- Data Wrangling: Experience reconciling data across inconsistent sources.
- Domain Interest: Genuine interest in developer-productivity tooling and AI-assisted engineering.
Education/Experience:
- Currently pursuing (or recent grad of) a Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field.
Physical Requirements:
- Prolonged periods of sitting/standing at a desk and working on a computer.
- The employee is routinely required to sit, stand, walk; talk and hear; and use hands to keyboard.
- Specific vision abilities required by this job include close vision, color vision, peripheral vision, depth perception, and ability to adjust focus.
- Ability to lift 20 lbs.