AI Product Engineer

As an AI Product Engineer at Windsurf, your responsibilities include proposing and building innovative AI-powered experiences tailored to millions of developers, especially professional software engineers working within Fortune 500 companies. You will work with complex AI systems focused on code generation and context retrieval, ensuring the delivery of efficient and scalable code. You'll also independently manage product experiments, track their effects, and document your findings to enhance overall product efficacy.

To qualify for the position of AI Product Engineer at Windsurf, you should possess strong software engineering skills and a deep curiosity and passion for AI research and applications. Familiarity with AI-powered developer tools like the Windsurf Plugin, Copilot, and ChatGPT is a strong plus. Ideal candidates are self-starters who can independently manage projects, work collaboratively in a team, and have a keen interest in transforming AI innovations into practical solutions that enhance software development.

As an AI Product Engineer at Windsurf, you'll engage in exciting projects that involve deploying AI solutions for hundreds of thousands of active users across multiple IDEs. You'll work on various products, including our autocomplete and chat system that seamlessly integrates with popular repositories, and contribute to the development of a data processing framework designed to handle petabytes of information. You'll also have the opportunity to tackle challenges related to code attribution, ensuring generated code is properly licensed.

The team culture at Windsurf is built on trust, agency, and ownership, where AI Product Engineers are encouraged to take the lead on their projects. You’ll work closely with other passionate individuals in a collaborative environment, where knowledge-sharing and code reviews are integral parts of our daily routine. We believe that the best work comes from in-person collaboration, and we foster an environment that values creativity and innovation without strict oversight.

At Windsurf, we understand that research serves to enhance our products. While keeping up with the latest AI papers is important, our focus is on practical applications within our development process. AI Product Engineers combine excellent software engineering skills with insights from research to create a powerful and effective user experience. This means you'll continuously translate cutting-edge research into actionable improvements in our AI tools.

When answering, focus on specific tools you've used, such as the Windsurf Plugin, Copilot, or ChatGPT. Highlight your hands-on experiences and how these tools have influenced your development process. Discuss any projects where you've integrated such tools and the impact they had on efficiency and code quality.

Discuss your process for identifying user needs and translating them into product features. Mention methods for gathering feedback, conducting user tests, and iterating based on results. Also, highlight any frameworks or tools you use to ensure scalability and efficiency in your designs.

Be prepared to discuss any projects where you've implemented or created context-retrieval algorithms or worked on code generation. Highlight the challenges you faced and how you overcame them, showing a clear understanding of the importance of context in AI applications.

Choose a project where you took the initiative to identify a problem, researched potential solutions, and executed the project from start to finish. Explain your decision-making process, how you tracked progress, and what you learned from the experience.

Highlight your acceptance of constructive criticism during code reviews and your approach to iterative improvement. Provide examples of feedback that influenced your work and how you integrated suggestions to enhance your coding practices.

Articulate your passion for AI technology and its transformative potential in software development. Discuss specific trends or innovations that excite you and how you strive to incorporate them into your work to push boundaries and enhance efficiency.

Discuss methods you use to stay informed, like attending conferences, participating in online communities, or following relevant publications. Share how you’ve applied what you learned to your projects, ensuring your skills remain current and impactful.

Explain your analytical approach to interpreting product experiment results, focusing on the metrics you track, tools you might use for analysis, and how you document findings to inform future projects. Illustrate this with a specific example of how data-driven insights shaped a product decision.

Mention tools and methods you use for collaboration, such as Agile methodologies, regular stand-ups, or brainstorming sessions. Highlight your adaptability in working with team members to synthesize ideas and reach consensus on product direction.

Share your strategies for prioritization, such as assessing impact versus effort, user feedback, or business goals. Discuss how you remain organized and focused on vital tasks while staying flexible to shift priorities as needed.