• Collaborate with Product to determine application structure, define entity/data models, specify task workflows, and define desired data visualization experiences • Create registration entities, data flows, task templates, data visualization experiences, and other configurations in support of developing Luma Solutions • Perform in-team testing of configuration and assist is handing test cases to the QA group for release testing • Write draft documentation of configuration and workflows and collaborate with the Documentation team • Train members of other Dotmatics teams and early customers on how to use Luma Solutions configuration and the workflows it supports • Use new product features in Luma Solutions and provide feedback on the experience • Actively participate in the development of best practices for Luma configuration and ensure these best practices are followed

• Collaborate with Product to determine application structure, define entity/data models, specify task workflows (Scientific Workflows), and define desired data visualization experiences • Create registration entities, data flows, task templates, data visualization experiences, and other configurations in support of developing Luma Solutions • Perform in-team testing of configuration and assist in handing test cases to the QA group for release testing. Troubleshoot configuration to understand why it is not producing desired results. • Write draft documentation of configuration and workflows and collaborate with the Documentation team to develop final customer-facing documentation • Train members of other Dotmatics teams and early customers on how to use Luma Solutions configuration and the workflows it supports • Use new product features in Luma Solutions and provide feedback on the experience, participate in user experience testing, and provide input to the Product team about features that will enable the best Solutions • Actively participate in the development of best practices for Luma configuration, and ensure these best practices are followed in the development of Luma Solutions

Role Description We are looking for a Principal Product Manager for Agentic AI Infrastructure to define and own the product strategy for a new generation of managed agent infrastructure products. This role will shape one or more products like: - Open Harness Server - Code Execution Sandbox - Action Gateway This is a rare opportunity to help define a new product category at DigitalOcean and build the infrastructure layer that agent-native companies will depend on. What You’ll Do - Define the Agentic AI infrastructure product strategy: - Own the product vision, roadmap, and execution plan for DigitalOcean’s managed agent infrastructure products. - Build foundational agent infrastructure products: - Lead product definition for services such as Open Harness Server, Code Execution Sandbox, Action Gateway, tool execution, session management, agent runtime APIs, and related developer experiences. - Work backwards from agent-native customers: - Partner directly with companies building coding agents, productivity agents, workflow agents, and custom AI systems to understand the infrastructure they need to move from prototype to production. - Create simple abstractions for complex workloads: - Define product experiences that make it easy for developers to run long-lived agents, fork sessions, resume work, attach tools, manage credentials, execute code safely, and observe agent behavior. - Shape the developer experience: - Build intuitive APIs, CLIs, docs, examples, and workflows that let developers bring their existing harnesses and agent frameworks to DigitalOcean with minimal friction. - Partner with engineering on architecture and tradeoffs: - Work closely with engineering leaders to translate customer needs into product requirements across MicroVMs, sandboxing, tool execution, identity, state management, observability, security, and scale. - Launch new products and SKUs: - Partner with GTM, finance, and engineering to define packaging, pricing, beta programs, launch plans, and adoption motions for agentic infrastructure services. - Drive operational and business outcomes: - Establish product metrics around adoption, retention, usage, reliability, workload scale, gross margin, developer satisfaction, and revenue growth. - Evangelize the category: - Help DigitalOcean explain why agents need a new infrastructure layer and how our products help developers build, test, deploy, and operate agents with confidence. Qualifications - Strong product leadership in infrastructure or developer platforms. - Fluency in agentic AI systems. - Technical depth in cloud primitives. - Customer-backed product instincts. - Strong systems thinking. - Developer empathy. - Business judgment. - Executive communication and influence. - Category-building mindset. Compensation Range $215,200 - $269,000 This is a remote role Benefits - Competitive array of benefits to support well-being, including an Employee Assistance Program and flexible time off policy. - Reimbursement for relevant conferences, training, and education. - Access to LinkedIn Learning's 10,000+ courses for continued growth and development. - Bonus eligibility based on company and individual performance. - Equity compensation to eligible employees, including equity grants upon hire and participation in the Employee Stock Purchase Program. Company Description 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.

• Build and mature the Context Layer by defining the structured intelligence architecture that gives Active Intelligence a deep understanding of each customer's goals, brand, and audience behavior. • Architect the Deep Reasoning Agent using frontier model capabilities (extended thinking, multi-step research) to deliver deep analytical insights that make static reporting obsolete. • Connect the product flywheel to ensure a continuous loop where richer context drives more powerful reasoning, fueling deeper user engagement. • Design robust evaluation frameworks, golden sets, and quality rubrics to rigorously grade agent outputs and establish the bar for true "marketing-grade intelligence". • Operate as a technically credible builder, prototyping directly with frontier models and testing prompt architectures as a peer to our applied AI and ML engineers. • Collaborate cross-functionally across data/ML teams, the agent platform, and the broader product organization to move people and align goals without relying on positional authority. • Drive continuous improvement in model behavior and data structures, balancing technical elegance with ultimate customer value.