DigitalOcean
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Principal Engineer, Managed Agents

Principal Engineer, Managed Agents

DigitalOcean

Seattle, WA • Hybrid

$227K - $283K/yr

Other

Posted yesterday


Job description

AI coding agents are changing how software gets written. The infrastructure to run them reliably in production - persistent memory, cost controls, isolated execution, full observability - is still being built. That's what this team is solving.

As Principal Engineer for Managed Agents, you'll own the technical architecture of DigitalOcean's agent runtime platform: session lifecycle, memory, execution isolation, and the developer experience that ties it together. This is a company-level IC role - you'll set direction for multiple teams, influence the product roadmap, and define what production-grade agent infrastructure looks like at a company with the infrastructure depth and developer trust to make it real.

What You'll Do:Define the architecture
  • Own the long-term technical design of the agent runtime: session lifecycle, memory persistence across sessions, execution isolation, and agent-to-tool interaction.
  • Drive the memory layer - short-term context, long-term structured memory, episodic recall - ensuring it's reliable and practical for real production workloads.
  • Set the bar for how coding agents integrate with developer infrastructure: repositories, CI/CD, and existing developer workflows.
Lead across the company
  • Build alignment across engineering pillars on a shared technical direction - resolving conflicts and maintaining momentum on a platform that spans infrastructure, AI, and developer experience.
  • Partner with product to shape the multi-year strategy, not just the current release.
Build DigitalOcean's position externally
  • Represent DigitalOcean in the agent infrastructure space through conference talks, open-source engagement, and relationships with the framework teams whose work runs on this platform.
  • Inform ecosystem partnerships and vendor decisions with technical depth and strategic judgment.
Raise the technical bar
  • Be the technical north star for Staff and Senior engineers across the Managed Agents org - coaching on architecture, tradeoffs, and what good looks like.
  • Define engineering standards for how DigitalOcean builds, ships, and monitors production agent systems.
What You'll Add to DigitalOcean

You've built production infrastructure developers trust at scale. You're technically exceptional and organizationally effective. You likely bring:

  • 12+ years building production infrastructure, AI/ML systems, developer tools, or cloud platforms - shipping things developers depend on at scale.
  • Deep expertise in agent memory systems (retrieval, long-term context, grounding) or AI coding assistance (code understanding, execution environments, developer workflow integration).
  • Experience with distributed systems lifecycle management: session persistence, state snapshotting, execution isolation, or multi-tier storage.
  • A track record of driving technical decisions across multiple teams - not just recommending, but executing across organizational boundaries.
  • The ability to communicate a technical vision to engineers, executives, and industry audiences - and make each one trust it.
  • Strong software engineering in Python and at least one production systems language. You still write code.
Preferred Qualifications:Strong signal
  • Prior Principal Engineer, Distinguished Engineer, or equivalent IC - with company-level impact, not just team or pillar.
  • Experience building developer infrastructure: cloud runtimes, execution sandboxes, CI/CD systems, or platforms other engineers build on top of.
  • Hands-on experience with agent memory or retrieval in production: RAG, semantic search, knowledge graphs, or long-term session context.
  • External technical leadership: conference talks, open-source ownership, publications, or standards work in AI infrastructure or developer tooling.
Nice to have
  • Master's or PhD in CS, distributed systems, ML, AI, or equivalent depth through industry work and public contributions.
  • Experience with virtualization primitives: microVMs, Firecracker, gVisor, or OCI runtimes.
  • Familiarity with agent frameworks in production: LangGraph, CrewAI, Claude Agent SDK, OpenAI Agents SDK, or similar.
  • Patents, publications, or significant open-source work in agent systems, cloud infrastructure, or applied ML.
Compensation Range:
  • $227,040 - $283,800

*This is a hybrid role

JR: 2025-7060

#LI-Hybrid