Software Engineering Intern, Developer Productivity

Job description

This is a 3-month onsite internship in Redwood City, CA. We are looking to fill this role immediately. 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. 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.