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 Staff 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.
- 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.
- Create leverage for the broader engineering organization through reusable patterns, technical standards, documentation, and coaching.
- Provide technical leadership on projects by breaking down ambiguous problems and guiding engineers toward clear execution plans.
- Support the growth of junior and mid-level engineers through coaching, pairing, and constructive feedback.
- Foster a culture of ownership, accountability, and continuous learning across the team.
- Lead by example in incident response, operational readiness, and production-quality engineering practices.
- 8+ 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
- 2+ years of hands-on experience with Go / Golang in production systems
- 2+ 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.
- 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
- $167,200.00 - $209,000
*This is a remote role
JR: 2026-7593
#LI-Remote
- 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.
Skills Required
- 5+ years of experience in high-performance computing or AI infrastructure
- Deep familiarity with Gen AI landscapes including LLM, VLM, LMM
- Hands-on experience with attention-layer optimizations and parallelization strategies
- Comprehensive understanding of NVIDIA and AMD GPU architectures
- Experience integrating and building open-source software projects
- Excellent system design skills related to low-level GPU programming
- Experience acting as a technical lead
DigitalOcean Compensation & Benefits Highlights
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Healthcare Strength — Health coverage is described as market‑leading across medical, dental, vision, and mental‑health, with company‑paid life and income‑protection. This positions core healthcare and protection benefits as a standout element of the package.
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Parental & Family Support — Parental leave is characterized as above‑average, frequently highlighted alongside a phased return‑to‑work program. This indicates strong support for new parents beyond baseline policies.
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Equity Value & Accessibility — The package includes recurring equity grants and access to an Employee Stock Purchase Plan. This provides meaningful ownership opportunities alongside cash compensation.
DigitalOcean Insights
What We Do
DigitalOcean is the Inference Cloud — a full-stack, production-ready cloud platform built to run AI applications with predictable performance, sustainable economics, and radically simpler operations at scale. We are built for teams turning AI into real products — not just training models. Our advantage is not fewer features, but fewer failure modes when operating AI at scale — combining minimal operational overhead, predictable cost efficiency, and a full-stack cloud that works as a system. Hyperscalers are broad by design. Neoclouds are infrastructure-first. DigitalOcean is inference-first — with a real cloud underneath. It combines inference-optimized compute, managed inference software, and integrated cloud capabilities that reduce operational burden for teams running real workloads. Inference is the foundation—not the boundary. Everything else builds on top of it.
Why Work With Us
At DO, we do career-defining work. We innovate with AI and build cutting-edge tech. Our rewards to match that intensity - to motivate you, recognize your impact, and give you what you need to thrive. If you have a growth mindset, like to think big and bold, and are energized by the fast-paced environment, you'll find your place here.
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DigitalOcean Offices
Remote Workspace
Employees work remotely.
We commit to both remote work and in-person collaboration. These ways of working are dependent on specific roles and are mutually agreed upon by employees. In the US, we are mainly remote. In our APAC locations, we have a hybrid in-office approach.
