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DigitalOcean

Runs cloud infrastructure for apps and AI

Senior Software Engineer 2 - Network Datapath

Full-Time
$167.2k - $209k+ Bonus + Equity grants + Employee Stock Purchase Program
Senior
Seattle, WA, USA
Hybrid
Software EngineeringSystems Software Engineering

About the job

Requirements
  • Strong experience designing and developing production software in C, C++, or Go.
  • Strong understanding of networking and packet processing.
  • Experience developing software for Linux-based networking systems.
  • Solid understanding of networking concepts including TCP/IP, routing, switching, VLANs, VXLAN, BGP, ECMP, NAT, load balancing, and network virtualization.
  • Experience debugging and optimizing performance-sensitive systems.
  • Understanding of Linux networking internals, including the Linux kernel networking stack, network namespaces, sockets, queues, interrupts, and NIC drivers.
  • Experience with one or more high-performance networking technologies such as DPDK, XDP, eBPF, AF_XDP, or SR-IOV.
  • Experience with multithreaded and concurrent software.
  • Strong understanding of performance analysis, profiling, benchmarking, and troubleshooting.
  • Ability to reason about complex systems across hardware, operating systems, networking, and applications.
  • Ability to independently drive projects from technical design through implementation and production deployment.
  • Strong technical writing skills, including producing RFCs, architecture/design documents, technical proposals, and other documentation required to drive engineering projects.
  • Strong communication skills and ability to work effectively across engineering teams.
  • Use AI and modern engineering tools to increase personal and team leverage and accelerate delivery.
Responsibilities
  • Design, develop, and optimize high-performance network datapath software for DigitalOcean's cloud infrastructure.
  • Build and improve packet-processing and forwarding systems focused on throughput, latency, CPU efficiency, scalability, and reliability.
  • Develop networking functionality across the host, kernel, user space, and hardware-accelerated datapath.
  • Work with Linux networking, eBPF, XDP, DPDK, AF_XDP, SR-IOV, and programmable datapaths.
  • Analyze packet-processing paths and identify opportunities to eliminate bottlenecks and improve performance.
  • Develop software for routing, packet filtering, encapsulation, tunneling, load balancing, traffic steering, and network virtualization.
  • Build and improve datapath observability, telemetry, debugging, and performance monitoring.
  • Design software that integrates with DPUs, SmartNICs, programmable NICs, and other hardware acceleration technologies.
  • Develop automated testing and benchmarking frameworks to validate datapath correctness and performance.
  • Investigate complex production networking issues, including packet drops, latency, throughput degradation, CPU utilization, and unexpected traffic behavior.
  • Work with Network Infrastructure and Compute engineers to integrate datapath functionality into DigitalOcean's broader infrastructure architecture.
  • Contribute to the design and implementation of next-generation network architectures.
  • Author RFCs, architecture documents, technical proposals, design documents, and implementation plans to drive complex networking initiatives.
  • Document technical decisions, tradeoffs, performance characteristics, dependencies, and operational considerations.
  • Participate in design reviews and provide technical guidance to other engineers.
  • Mentor engineers and contribute to improving software engineering and networking practices across the organization.
  • Own significant technical components and deliver them from design through production.
  • Solve complex performance and reliability problems in the network datapath.
  • Make sound technical decisions based on measurable performance and operational requirements.
  • Develop scalable solutions rather than one-off fixes.
  • Proactively identify architectural and performance bottlenecks.
  • Work effectively across Network Infrastructure, Compute, Security, and other engineering organizations.
  • Produce clear RFCs and technical documentation that enable teams to align on complex architectural decisions.
  • Mentor other engineers and raise the technical bar within the team.
Desired Qualifications
  • Experience with hardware-accelerated networking, including developing software for DPUs, SmartNICs, IPUs, or programmable NICs.
  • Understanding of how functionality can be distributed between host CPUs, NICs, DPUs, and switches.
  • Experience with DPU-based networking, security, storage, virtualization, or packet processing.
  • Experience with programmable datapaths such as P4, eBPF, or other programmable data-plane technologies.
  • Understanding of PCIe, DMA, queues, interrupts, RSS, offloads, and NIC hardware architecture.
  • Experience working on cloud networking or hyperscale infrastructure.
  • Experience developing Linux kernel networking code or NIC drivers.
  • Experience with DPDK, XDP, eBPF, AF_XDP, or DPU-based datapaths in production.
  • Experience with 400G+ networking.
  • Experience with high-performance packet processing at 10/25/40/100/200/400G+ speeds.
  • Experience with network virtualization and overlay technologies such as VXLAN/EVPN.
  • Experience with programmable switches.
  • Experience with performance analysis using tools such as perf, eBPF tooling, flame graphs, or hardware performance counters.
  • Experience building network datapath tests and benchmarking infrastructure.
  • Contributions to Linux, DPDK, eBPF, OVS, or other networking/open-source projects.

About the company

DigitalOcean provides cloud infrastructure for developers and businesses to build, host and scale applications and AI services. Teams rent virtual machines called Droplets, store data and run managed databases or Kubernetes clusters through a web console and APIs. Its AI services supply GPU computing, model inference and managed environments where software agents use tools and retain information between sessions. Customers pay for the resources they use, with subscriptions and managed services helping teams run applications without maintaining all the underlying infrastructure themselves. DigitalOcean was founded in 2012 and is headquartered in Broomfield, Colorado.

Company Size

1,001-5,000

Company Stage

IPO

Headquarters

Broomfield, Colorado

Founded

2012

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Simplify's Take

What believers are saying

  • Revenue is accelerating: DigitalOcean's August 2026 report showed Q2 revenue of $281 million, up 29% yearly.
  • AI demand is scaling: DigitalOcean's August 2026 report put AI Customer ARR at $234 million, up 212% yearly.
  • Learning receives funding: DigitalOcean's US rewards page offers education reimbursement and one professional development book per month.

What critics are saying

  • Expansion uses borrowing: DigitalOcean secured a $725 million equipment financing facility in September 2026, maturing in 2030.
  • Cloud competition is broad: DigitalOcean's annual filing names AWS, Azure and Google Cloud alongside smaller providers targeting similar customers.
  • Infrastructure work extends after hours: DigitalOcean's live Wenatchee data center manager role requires onsite work and on-call escalations.

What makes DigitalOcean unique

  • Entry costs are bundled: DigitalOcean's $4 monthly Basic Droplet includes 500 GiB of outbound transfer.
  • Agent spending gets discounts: DigitalOcean's October 2026 preview subscriptions apply 15% or 20% discounts until the monthly balance runs out.
  • Agent sessions are isolated: DigitalOcean's September 2026 Managed Agents preview gives each session its own runtime and governed tools.

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Benefits

  • Remote-first
  • Full health coverage
  • Wellness coverage
  • Flexible vacation time
  • Team-building & social events
  • 401(k) plans
  • ESPP
  • Education support
  • Partner support
  • Employee giving

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

1%

2 year growth

0%
Yahoo Finance
Oct 15th, 2026
DigitalOcean and HCI are growth stocks to buy, while Glacier Bancorp faces headwinds

StockStory has named two growth stocks to buy and one to avoid, citing revenue trends and valuations. DigitalOcean (NYSE:DOCN) grew revenue 21.4% over the past year. Billings growth averaged 25.2%, and analysts expect 40.7% sales growth over the next 12 months. The stock trades at $107.63, or 11.4x forward price-to-sales. HCI Group (NYSE:HCI), a Florida property insurer, grew revenue 22.8%. Its earnings per share rose 36.3% annually over two years, and book value per share grew 42.4%. It trades at $195.79, or 2x forward price-to-book (P/B). StockStory advises selling Glacier Bancorp (NYSE:GBCI), whose revenue grew 31.7% last year. Over five years, however, revenue growth averaged 8.5% annually and earnings per share fell 4.8% annually. The stock trades at $42.72, or 1.3x forward P/B.

Business Wire
Oct 13th, 2026
Newsroom | Business Wire

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Business Wire
Oct 13th, 2026
Newsroom | Business Wire

The global leader in press release distribution and regulatory disclosure. Public relations and investor relations professionals rely on Business Wire for broad-based and targeted market reach.

MarketScreener
Oct 12th, 2026
Digitalocean launches Agent Learning and Data Services for recursively self-improving ai agents.

Digitalocean launches Agent Learning and Data Services for recursively self-improving ai agents. Published on 10/12/2026 at 05:48 pm EDT S&P Capital IQ DigitalOcean announced Agent Learning and Data Services as another key element of its modern agentic stack, so teams can launch self-improving agents. Together with Inference Engine and Managed Agents, DigitalOcean is one of the few clouds where agents can run, learn, and improve on one platform. Agent Learning Services give every team that loop in one place. Insights records every step an agent takes, and Signals flags the sessions that matter: where the agent stalled, looped, lost the user, or failed. That evidence becomes a proposed change. Evaluations and Simulations test changes ahead of real users with realistic conversations built from flagged sessions. Each change feeds the next stage of the loop. This recursive self-improvement is available for models: the newly enhanced Inference Router picks the best-scoring model for each task, optimized for cost, quality, or the team?s own evaluations, and re-runs those evaluations as new models ship. Agent Data Services is the data layer the loop runs on, and the one agents work from. Every piece of a company?s data becomes agent-ready the moment it arrives. Video is transcribed and described, documents are read and indexed, logs and agent sessions are assembled with configurable redaction controls for sensitive details, and all of it is searchable by meaning in a single call. It lands in one catalog, designed to be logically isolated to that customer, with governance designed so that only authorized people and agents can reach each piece of data. Agent Learning Services are built on it: Signals writes sessions into it, and Optimizer draws its training and test data from it only where the customer expressly opts in. The same platform serves far more than the learning loop. Teams can use it for search and analytics across video, audio, documents, and structured data, and for grounding any agent in the company?s own records. Agent Learning Services (Insights, Signals, and Evaluations and Simulations) are available in public preview. Inference Router optimizer and Agent Data Services are available in private preview. DigitalOcean will demonstrate the services live at the Open Intelligence Summit on Oct. 13 in San Francisco. (C) S&P Capital IQ - Business Wire - 2026

Associated Press
Oct 12th, 2026
DigitalOcean launches learning and data services for self-improving AI agents

DigitalOcean (NYSE: DOCN) has launched Agent Learning Services and Agent Data Services, which let companies build AI agents that improve themselves. The cloud provider announced the products ahead of its Open Intelligence Summit in San Francisco. Learning Services record what an agent does, flag where it fails, and test fixes before customers see them. Data Services give agents one managed place to read context and write back what they learn. The enhanced Inference Router already applies this loop to models, picking the best-scoring one for each task. DigitalOcean plans to extend it to agent workflows. Learning Services are in public preview. Data Services and the Inference Router optimizer are in private preview.