Jobs at DigitalOcean

Lead full-lifecycle technical recruiting for cloud, infrastructure, AI, and platform engineering roles. Partner with senior engineering leaders on workforce planning, manage complex pipelines, source specialized talent through multiple channels, advise on compensation and market conditions, and execute talent programs. Analyze recruiting metrics, improve workflows and interviewer calibration, use Greenhouse and modern recruiting technologies, and close executive-level candidates across global environments.

Leads the strategy, architecture, and deployment of AI-enabled business intelligence infrastructure. Designs governed semantic layers, data models, and BI systems using dbt and enterprise data warehouses. Manages and coaches a technical engineering team, partners with executives and cross-functional stakeholders, and ensures reliable, high-performing data pipelines, warehouses, and reporting tools. The role also advances AI-driven analytics, data discovery, and self-service reporting across the organization.

Leads complex technical infrastructure programs spanning data center build-outs, hardware deployment, capacity planning, and AI cloud infrastructure. Partners with Product, Engineering, supply chain, facilities, vendors, and networking teams to manage delivery, risks, dependencies, scope changes, and stakeholder communication. Builds scalable processes, coordinates off-site physical work, drives consensus, and improves program execution across global locations.

Develop and operate scalable DNS control-plane software and APIs for DigitalOcean’s network products. Responsibilities include implementing, testing, optimizing, and supporting distributed services; improving performance, monitoring, reliability, and customer experience; collaborating across networking teams; establishing engineering best practices; and operating Linux-based hosts. The role requires Go development, cloud and containerization experience, API and database design, CI/CD, and knowledge of DNS and networking.

Design, implement, test, and optimize scalable control-plane and data-plane services for cloud networking products. Build APIs, distributed systems, monitoring tools, and performance improvements while supporting existing products. Establish engineering best practices, improve reliability and delivery processes, collaborate across teams, and mentor engineers. The role requires strong Go development, networking expertise, cloud and containerization experience, and familiarity with technologies including eBPF, XDP, gRPC, Kafka, and Kubernetes.

Develop and optimize high-performance network datapath software for cloud infrastructure. Build packet processing, routing, forwarding, load balancing, observability, and hardware-accelerated networking across Linux hosts, kernels, user space, NICs, DPUs, and SmartNICs. Diagnose production performance issues, create testing and benchmarking frameworks, author technical designs, collaborate across infrastructure teams, and mentor engineers.

Develop and maintain scalable control-plane software for cloud networking products. Responsibilities include building APIs and services, testing and optimizing systems, troubleshooting customer issues, improving reliability and performance, collaborating across networking teams, supporting existing products, and establishing development and architecture best practices. The role uses Go and distributed-systems technologies including Kubernetes, Docker, Kafka, gRPC, and Prometheus.

Design and build software for global network automation, orchestration, provisioning, device lifecycle management, telemetry, validation, and automated remediation. Integrate DPUs, SmartNICs, and programmable network infrastructure into scalable cloud systems. Establish architecture and technical direction, write RFCs and design proposals, lead complex initiatives from concept through operation, mentor engineers, and collaborate across network, infrastructure, hardware, compute, storage, and security teams.

Lead development of high-performance distributed control plane services and microservices using Go. Drive complex projects from design through release, solve distributed systems challenges, mentor engineers, improve architecture and operational workflows, and support production systems through on-call monitoring and incident response.

Leads DigitalOcean’s Virtual Networking organization and multi-year strategy. Oversees architecture, development, reliability, security, and operation of cloud-scale networking services including VPC, DNS, gateways, DDoS protection, and firewalls. Builds and mentors engineering teams, drives operational excellence, partners across engineering and product, and shapes networking investments supporting global infrastructure and AI workloads.

Own technical revenue accounting for complex customer, partnership, and marketplace arrangements, including ASC 606 assessments, variable consideration, contract modifications, and revenue recognition. Partner cross-functionally with Sales, Legal, Product, Engineering, Billing, and Finance to operationalize new monetization models, improve controls, support close and reporting, and lead scalable process, system, automation, and AI-enabled enhancements.

Design and build scalable Go-based distributed control plane microservices for cloud compute infrastructure. Develop gRPC interfaces, optimize Linux kernel and virtualization systems, and improve performance, reliability, observability, failover, and recovery. Lead complex cross-functional technical projects, mentor engineers, conduct architectural reviews, support production systems through on-call rotations, and drive continuous improvements across the Compute ecosystem.

Lead secure design reviews, threat modeling, and security risk assessments for products and features. Partner with engineers, product managers, and designers to develop secure architectures, provide remediation guidance, promote security culture through training and mentoring, oversee vulnerability management, and explain security events. Build security tooling, automate secure development practices, and establish architectural patterns and processes that reduce security risk across DigitalOcean’s engineering organization.

Leads DigitalOcean’s Applied Research function for agentic AI, setting the research agenda across model routing, memory, observability, and reinforcement learning. Builds and manages a research team, connects research investments to product outcomes, and partners with engineering to ship production capabilities that improve reliability, cost, latency, and task success. Represents the company externally through publications, talks, open-source work, and research collaborations.

Drive technical infrastructure programs spanning data center build-outs, hardware deployments, capacity planning, and operational initiatives. Coordinate Product, Engineering, infrastructure teams, supply chain, facilities, vendors, and networking groups. Own planning, execution, risk management, stakeholder alignment, communication, follow-through, and process improvement to deliver cloud and AI infrastructure reliably and efficiently.

Lead DigitalOcean’s AI security strategy, governance framework, threat modeling, and multi-year roadmap. Partner with security, engineering, and data science teams to secure AI products, deploy guardrails, conduct adversarial testing and red teaming, and monitor AI/ML systems. Provide architectural reviews, executive risk briefings, and guidance on emerging threats including prompt injection, model supply-chain risks, agentic AI, and data exfiltration.

Designs and scales data center hardware platforms and automation across DigitalOcean’s infrastructure. Responsibilities include leading hardware design and vendor projects, developing hardware roadmaps, automating configuration and validation, troubleshooting fleet hardware as a Tier 3 escalation, supporting 24/7 on-call operations, improving firmware and hardware automation, collaborating with vendors, and mentoring engineers. The role requires deep server architecture, Linux, networking, storage, firmware, configuration management, and large-scale hardware automation expertise.

Leads complex technical programs from prioritization and planning through execution and success measurement. Partners with Product and Engineering leaders, aligns stakeholders across teams and locations, manages risks, scope changes, impediments, and conflicts, and drives consensus and continuous process improvement. Promotes scalable program-management practices while ensuring timely delivery of valuable products aligned with company objectives.

Design and optimize scalable, multi-tenant serverless inference infrastructure and APIs for large-scale AI workloads. Build highly available distributed services, improve GPU utilization, observability, capacity management, fault tolerance, and operational automation. Partner with platform and GPU infrastructure teams, contribute to architecture decisions, participate in on-call and incident response, and provide technical leadership and mentorship to engineers.

Own technical go-to-market for AI-native cloud products and market segments. Translate complex capabilities into narratives, build demos and code, create technical content, run launches, enable sales, monitor market/competitive signals, and engage developer communities to drive adoption, pipeline, and wins.