Jobs / United States / Horizon3 AI B.V.

Horizon3 AI B.V.

Senior Backend Engineer, Autonomous Defense

US, Remote · Remote · US only Posted 1 month ago

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Skills this job asks for

CybersecurityAuditData engineeringGraphQLAccounting

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Where you can work from

United States only

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Sponsorship verdict

No sponsorship evidence yet

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  • No government sponsor record hereThis employer does not appear with approvals in the government data SponsorApply holds.
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  • No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
  • Confirmed live todayWhen a source last listed this job as open.
Details and sources
No salary bar for this route
H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.

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Before you apply

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About the role

Get to Know Us Horizon3 is a fast-growing, remote cybersecurity company dedicated to the mission of enabling organizations to proactively find and fix and verify exploitable attack vectors before criminals exploit them. Our flagship product, the NodeZeroTM platform, delivers production-safe autonomous pentests and other key assessment operations that scale across the largest internal, external, cloud, and hybrid cloud environments. NodeZero has been adopted by organizations of all sizes, from small educational institutions to government agencies and Global 100 enterprises. It is used by ITOps/SecOps teams, consulting pentesters, and MSSPs and MSPs.  We are a fusion of former U.S. Special Operations cyber operators, startup engineers, and formerly frustrated cybersecurity practitioners. We're committed to helping solve our common security problems: ineffective security tools, false positives resulting in alert fatigue, blind spots, "checkbox” security culture, cybersecurity skills shortage, and the long lead time and expense of hiring outside consultants. Collectively, we are a team of learn it alls, committed to a culture of respect, collaboration, ownership, and results.   What You'll Do As a Senior Backend Engineer on the Autonomous Defense team, you'll build the platform that NodeZero's defensive agents run on. Our AI researchers define what these agents should reason about, you build the systems that make that work in production, across thousands of customer tenants, without breaking anything. That means real distributed systems problems, not glue code. They execute inside customer environments under tight isolation, credential, and egress constraints. And when an agent proposes a change in production, the platform has to be able to simulate it, stage it, gate it on approval, roll it back, and prove after the fact exactly what happened and on whose authority. This is a platform role. You'll own the runtime, the tool layer, the orchestration, the connector framework, and the observability that makes agent behavior debuggable. You'll work closely with our AI researchers, but you are not being hired to tune prompts — you are being hired to build the substrate that makes their work shippable and safe. Responsibilities - Build and own the agent execution runtime: durable, resumable, long-running workflows with checkpointing, idempotent steps, cancellation, and timeouts at both the step and run level. - Design and implement the tool layer that agents act through — a registry with versioning, schema validation, per-tenant enablement, and authorization enforced server-side rather than by the model. - Build the connector framework for third-party security control planes (EDR, firewall, identity, SIEM, cloud IAM). - Implement the safe-change pipeline: dry-run and simulation, blast-radius classification, approval gates for high-impact actions, staged rollout, rollback, and an immutable per-tenant audit trail. - Extend NodeZero's tenant isolation model to agents that take write actions, covering execution boundaries, egress control, quotas, and cross-tenant leakage in caches, indexes, and logs. - Develop core product features in ETL and GraphQL to support data processing and retrieval for agent context, run history, and remediation state. - Build the ETL pipelines that turn pentest and remediation outcomes into the datasets our researchers train and evaluate against. - Instrument everything. Distributed tracing across an agent run, cost and token accounting per tenant, and the tooling to answer "why did the agent do that" without guessing. - Partner with AI researchers, attack engineers, and product to take capabilities from prototype to production, and feed platform constraints back into research direction

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