Staff Software Engineer: AI Inference Data Plane

About this role

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.

DigitalOcean is expanding its AI Infrastructure layer to support the next generation of AI-driven applications. We are seeking a Senior Engineer 2 to join our AI Inference Data Plane team. In this role, you will be a key technical leader responsible for designing, developing, and delivering high-scale, resilient data plane services that power our "Inference as a Service" offering. You will work at the intersection of distributed systems and specialized AI hardware to ensure our customers can deploy and scale their models with industry-leading performance and reliability. This is a hands-on role, requiring you to be able to develop high quality software while availing of all the productivity boosts granted by the latest AI coding agents.

What You’ll Do:

• Technical Leadership: Act as a technical leader on the team, driving the end-to-end design, development, and delivery of critical data plane components hosting large generative AI models.

• System Design: Architect and refine system design proposals for our high-scale, multi-tenant AI inference cloud ecosystem, ensuring they meet rigorous availability and resiliency standards.

• Performance Optimization: Implement and optimize distributed inference hosting using techniques like tensor/data parallelism, KV cache optimizations, and smart routing.

• Collaboration: Work cross-functionally with Product Managers, customer-facing teams, and other engineering teams to align technical roadmaps with customer needs.

• Distributed Serving at Scale: Build on Kubernetes-native distributed inference frameworks like llm-d (or alternatives such as NVIDIA Dynamo, Ray Serve, KServe) to deliver prefill/decode disaggregation, KV-cache-aware routing, tiered prefix caching, and wide expert parallelism for MoE models.

• Flow Control & Load Balancing: Solve the distributed-systems problems unique to LLM serving — inference-aware load balancing on queue depth, cache locality, and predicted latency; flow control and fairness across tenants; autoscaling inference pools; and moving gigabytes of KV-cache between prefill and decode instances with negligible overhead.

• Open Source Contributions: Contribute upstream to llm-d, vLLM, and the inference gateway ecosystem, and represent DigitalOcean in these communities.

• Mentorship: Coach and mentor junior engineers, fostering a culture of technical excellence and continuous improvement.

• Operational Excellence: Maintain and operate critical, high-scale services, utilizing observability tools and defining SLOs to ensure superior platform health.

What You’ll Bring to DigitalOcean:

• AI/ML Domain Knowledge: Hands-on experience hosting large language or multimodal models using inference engines like vLLM, SGLang, or TensorRT.

• Inference Frameworks: Familiarity with distributed inference serving frameworks such as llm-d, NVIDIA Dynamo, or Ray Serve.

• Inference Engine Depth: Hands-on experience with vLLM or alternatives (SGLang, TensorRT-LLM, TGI, Modular MAX), including internals like continuous batching, paged attention, and prefix caching.

• Distributed Inference Fluency: Understanding of why cluster-scale serving is hard: KV-cache locality is partitioned across workers, naive round-robin routing destroys cache hit rates and tail latency, and disaggregated prefill/decode requires fast cross-pod KV transfer (e.g., NIXL).

• Upstream Track Record: Merged contributions to vLLM, llm-d, SGLang, or similar projects strongly preferred.

• Architecture Proficiency: Knowledge of common LLM architectures and optimization techniques (e.g., continuous batching, quantization).

• Software Engineering: Expert-level proficiency in GoLang or Python and familiarity with gRPC.

• Cloud Operations: Proven experience shipping customer-facing software products and running critical services in a high-scale environment similar to DigitalOcean.

• Open Source Mindset: Experience integrating and building with open-source software.

Compensation Range:

• $167,200.00 - $209,000

*This is a remote role

JR: 2026-7593

#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 the same worldwide, specific benefits may vary based on local regulations and preferences.

• We reward our employees. The salary range f

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