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DigitalOcean

Runs cloud infrastructure for apps and AI

Senior Manager Data Center Design & Deployment

Full-Time
$156.8k - $196k+ Bonus + Equity grants + Employee Stock Purchase Program
Expert
Seattle, WA, USA
HybridHybrid role; expect 20–30% travel to active deployment sites globally.
Engineering ManagementEngineering Leadership

About the job

Requirements
  • At least 10 years in data center design, deployment, or infrastructure program management, including large-scale AI/GPU deployments.
  • At least 5 years leading design or deployment teams, including managing other managers.
  • Deep familiarity with GPU rack/cluster network topologies, including rail-optimized fabrics; structured cabling standards for copper and fiber, including MPO/MTP; and commissioning processes for high-density compute.
  • Hands-on experience with design and documentation tools such as AutoCAD, Visio, DCIM/NetBox or equivalent, and project/program management tools for tracking multi-site deployments.
  • Experience negotiating and managing third-party contractor and staffing vendor relationships, including statements of work and performance accountability.
  • A track record of building or scaling repeatable deployment processes across multiple sites or regions, rather than only executing a single build.
Responsibilities
  • Lead and grow a team of Design Engineers and Deployment Engineers/Managers across multiple concurrent global deployment programs.
  • Own floor layouts, rack elevations, cable routing diagrams, bills of materials, and installation packages for new builds, expansions, and hardware refreshes.
  • Develop and maintain point-to-point cabling standards, labeling conventions, and deployment documentation used across all sites.
  • Build and manage the master deployment schedule across concurrent projects, sequencing site readiness, hardware delivery, and contractor availability to meet committed go-live dates.
  • Own the deployment budget for programs, including contractor labor, equipment staging, and freight/logistics costs; report variances and forecast spending to leadership.
  • Source, qualify, and manage structured cabling and installation contractors and staffing vendors across all regions, including negotiating statements of work and holding vendors to quality and schedule commitments.
  • Partner with Data Center Engineering to ensure deployment packages comply with current electrical, mechanical, and safety standards before onsite work begins.
  • Partner with Network, Supply Chain, Construction, and Site Operations to align deployment timing with hardware delivery, facility readiness, and network turn-up.
  • Own commissioning and handoff criteria, define completion requirements before handoff to Site Operations, and apply those standards consistently across sites.
  • Run root-cause reviews on deployment defects and schedule misses, and drive process or documentation changes to prevent recurrence.
  • Establish and improve global deployment methodology, including playbooks, checklists, and training, to ensure consistent deployment quality across teams and contractors.
  • Develop design and deployment engineers through career growth planning and technical mentorship, and build a succession plan for key team roles.
  • Represent Design & Deployment in capacity planning and new-site scoping discussions, providing leadership with realistic lead times and staffing requirements.
  • Ensure designs from rack layout to network topology are future-proof and continuously enhanced.
  • Investigate and develop faster deployment methodologies.
Desired Qualifications
  • Strong cross-functional partnership skills to align Engineering, Network, Construction, Supply Chain, and Site Operations around a schedule.

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.