Senior Engineer II (Fleet Efficiency)
DigitalOceanAustin$168k – $210kPosted 24 February 2026
Job Description
Dive in and do the best work of your career at DigitalOcean. Journey alongside a strong community of top talent who are relentless in their drive to build the simplest scalable cloud. If you have a growth mindset, naturally like to think big and bold, and are energized by the fast-paced environment of a true industry disruptor, you’ll find your place here. We value winning together—while learning, having fun, and making a profound difference for the dreamers and builders in the world.
We are looking for an engineer who is passionate about maximizing the efficiency of the cloud hypervisor fleet while optimizing customer performance and availability.
The Fleet Efficiency team supports the scheduling of virtual machines, utilizing bin packing placement algorithms to maximize efficient use of the cloud’s resources. Additionally, we own automation dedicated to continuously monitoring and maintaining optimal use of resources, proactively addressing hypervisor maintenance, and supporting customer experience and performance. We’re looking for a skilled and motivated Software Engineer to join the Fleet Efficiency team. In this role, you will contribute to the design, development, and operation of the backend systems that support DigitalOcean’s core products. You will work closely with distributed systems, systems engineering, performance tuning, and observability to ensure our platform meets enterprise-grade reliability and usability.
What You’ll Do:
Spearhead the development of our distributed scheduling and optimization services
Develop robust scripts, tools, and automation solutions to streamline virtualization processes, enhance system performance, and boost operational efficiency.
Collaborate closely with a cross-functional, motivated team of three engineers located in the US and Canada
Utilize Golang, Linux, Kubernetes, bash, LibVirt, KVM, Python, MySQL
Solve interesting and complex problems in a technically rewarding environment
What You’ll Add to DigitalOcean:
Proven track record. 7+ years of experience developing, deploying, and managing distributed systems
Familiarity with concurrency and parallelism models in a modern programming language
Bonus: experience with gRPC, LibVirt, Kubernetes
Cultivate your skills, learn languages, and team up with an agile, self-motivated group of peers to design, develop, test and deploy software in modern tools and languages such as Go
Share responsibility for maintaining the availability and performance of core compute products
Solve interesting problems of complexity and scale in a technically rewarding environment
Compensation Range:
$168,000 - $210,000
*This is a remote role
#LI-Remote
Why You’ll Like Working for DigitalOcean
We innovate with purpose. You’ll be a part of a cutting-edge technology company with an upward trajectory, who are proud to simplify cloud and AI so builders can spend more time creating software that changes the world. As a member of the team, you will be a Shark who thinks big, bold, and scrappy, like an owner with a bias for action and a powerful sense of responsibility for customers, products, employees, and decisions.
We prioritize career development. At DO, you’ll do the best work of your career. You will work with some of the smartest and most interesting people in the industry. We are a high-performance organization that will always challenge you to think big. Our organizational development team will provide you with resources to ensure you keep growing. We provide employees with reimbursement for relevant conferences, training, and education. All employees have access to LinkedIn Learning's 10,000+ courses to support their continued growth and development.
We care about your well-being. Regardless of your location, we will provide you with a competitive array of benefits to support you from our Employee Assistance Program to Local Employee Meetups to flexible time off policy, to name a few. While the philosophy around our benefits is ... (truncated, view full listing at source)
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