Principle Software Engineer

Do you ever wonder what happens inside the cloud?

DigitalOcean (NYSE: DOCN) simplifies cloud computing so builders can spend more time creating software that changes the world. With our mission-critical infrastructure and fully managed offerings, DigitalOcean enables startups and small and medium-sized businesses (SMBs) to rapidly deploy and scale modern applications. As a remote-first organization, our employees, like our customers, are based around the world.

We are seeking a Principal Engineer who is deeply passionate about developing high-performance GPU Bare Metal solutions for AI/ML applications.

This role requires an expert in system architecture, performance optimization, and monitoring, committed to delivering solutions that meet rigorous standards for speed and reliability across distributed environments.

Key Areas of Focus:

• Develop a world-class GPU Bare Metal offering that surpasses customer expectations.
• Thrive in a dynamic, fast-paced environment focused on customer needs.
• Enhance system architecture and storage solutions, including Object, NFS, and block storage, to bolster GPU performance and scalability.
• Optimize monitoring and performance testing to guarantee high availability and excellence in operations.
• Lead the design and development of systems optimized for AI/ML workloads, focusing on speed and scalability.
• Promote a culture of continuous improvement and innovation, emphasizing speedy and high-quality project delivery.
• Utilize data analytics to drive performance enhancements and customer satisfaction.
• Demonstrate expertise in Agile methodologies to streamline project delivery.
• Balance speed with quality to deliver robust and scalable solutions.
• Champion the launch and growth of complex solutions that captivate and expand our customer base.
• Encourage continuous learning and a growth mindset within the team.

What You’ll Be Doing:

• Collaborate with our dedicated team to design, develop, and optimize a world-class GPU offering
• Define and refine infrastructure requirements needed to support AI/ML workloads.
• Develop and refine monitoring strategies to proactively manage system performance and reliability, ensuring high availability and operational excellence.
• Collaborate with technical leaders to store, move, and manipulate large datasets.
• Guide performance teams on industry-standard testing methodologies and help optimize for GPU fabric throughput.
• Identify security improvements and drive review discussions with internal teams.
• Influence a culture of engineering excellence through active engagement with DigitalOcean’s Architecture group.
• Work directly with engineering teams to deliver new infrastructure functions and technologies in support of DigitalOcean AI/ML products.
• Drive technical strategy influencing medium and long-term roadmaps.
• Contribute to open-source communities related to our stack and encourage your fellow sharks to do the same.
• Develop and integrate advanced storage solutions, including Object, NFS, and block storage technologies, ensuring their seamless performance and scalability within GPU infrastructure projects.

What We’ll Expect From You:

• Proven expertise in leading, developing, and scaling complex solutions from inception to global scale, emphasizing speed, quality, and customer satisfaction.
• Excellent leadership and collaborative skills, with a capacity to drive innovation in an Agile/Kanban environment.
• Demonstrated ability to develop and optimize complex storage and networking solutions.
• Strong strategic analytical skills to effectively utilize data, enhancing system stability and performance, and improving decision-making and problem-solving capabilities.
• Commitment to continuous learning and improvement, particularly in technologies that support AI/ML workloads.
• Always prioritize customer needs and feedback to drive product excellence.
• Ability to quickly adapt to new technologies and challenges.
• Excellent communication and collaboration skills to work effectively across teams.
• Understanding of AI/ML workloads and overall industry trends.
• Strong collaborator and consensus builder. Author and review design documentation.
• Experience troubleshooting, analyzing, and debugging.
• Experience as a software engineer/developer in a large-scale, distributed environment.
• Experience writing secure, testable, and robust low-level code.
• A critical thinker dedicated to solving problems and delivering solutions.
• Strong foundational experience in software development and architecture.