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DigitalOcean

Senior Engineer, Inference Control Plane

Posted Yesterday
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In-Office
Seattle, WA
139K-174K Annually
Senior level
In-Office
Seattle, WA
139K-174K Annually
Senior level
Design, build, and operate scalable, multi-tenant serverless inference services and APIs. Improve throughput, GPU utilization, reliability, and observability for large-scale AI workloads. Collaborate with platform, GPU infrastructure, and product teams, participate in on-call rotations, and drive architecture, automation, and incident reduction.
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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 seeking a Senior Engineer to implement and contribute to the design and optimization of our Serverless Inference infrastructure and APIs. In this role, you will tackle the challenges of large-scale AI workloads, focusing on throughput, GPU utilization, and fault tolerance to support next-generation inference needs of AI native enterprises.

What You'll Do:
  • Design and build scalable, multi-tenant services that power AI inference and intelligent routing workloads.
  • Develop and operate high-scale distributed systems with strong reliability, availability, and performance goals.
  • Strengthen platform resiliency through improved observability, capacity management, automation, and operational tooling.
  • Partner closely with platform, GPU infrastructure, and product engineering teams to deliver production-grade systems and highly available APIs.
  • Raise the engineering bar through strong software design, operational discipline, incident management, and continuous improvement practices.
  • Contribute to architecture decisions around traffic management, service orchestration, reliability, and platform scalability.
  • Participate in on-call rotations and lead efforts to reduce operator pain, improve service health, and prevent recurring incidents.
What You'll Bring:

Required 

  • 5+ years of experience building and operating multi-tenant platforms or distributed backend systems
  • Strong experience operating high-scale distributed services in production environments
  • Deep understanding of SRE principles, including observability, incident management, reliability engineering, capacity planning, and operational automation
  • 1+ years of hands-on experience with Go / Golang in production systems
  • 1+ years of experience with Kubernetes
  • Strong understanding of cloud-native architectures, microservices, and distributed systems fundamentals
  • Experience debugging performance, scalability, and reliability issues in production systems
  • Observability Proficiency: Experience tracking infrastructure and inference metrics like Time To First Token (TTFT), Time Per Output Token (TPOT), and GPU utilization.

Bonus 

  • AI/ML Framework Knowledge: Understanding of modern LLM serving architectures and familiarity with engines like vLLM or Triton.
  • Experience with API gateways, traffic routing, or service mesh technologies
  • Familiarity with LLM serving stacks such as vLLM, TensorRT-LLM, or similar technologies
  • Experience building systems for inference optimization, rate limiting, routing, or workload orchestration
Compensation Range: 
  • $139,000 - $174,000

*This is a hybrid role

JR: 2026-7622

#LI-Hybrid

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 the same worldwide, specific benefits may vary based on local regulations and preferences.
  • We reward our employees. The salary range for this position is based on market data, relevant years of experience, and skills. You may qualify for a bonus in addition to base salary; bonus amounts are determined based on company and individual performance. We also provide equity compensation to eligible employees, including equity grants upon hire and the option to participate in our Employee Stock Purchase Program.
  • DigitalOcean is an equal-opportunity employer. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.

Application Limit: You may apply to a maximum of 3 positions within any 180-day period. This policy promotes better role-candidate matching and encourages thoughtful applications where your qualifications align most strongly.

DigitalOcean Santa Clara, California, USA Office

3979 Freedom Cir, Suite 540, Santa Clara, CA, United States, 95054

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