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Horizon3.ai

Autonomous pentesting SaaS for vulnerabilities

Senior Full-Stack Engineer - Autonomous Defense

Full-Stack EngineeringConfirmed live in the last 24 hours
Full-timeRemote in USA

About the Job

Requirements

  • A bachelor's degree in Computer Science, Computer Engineering, or a related field is required.
  • At least 7 years of professional software engineering experience using modern object-oriented or functional languages such as Python, Go, Scala, C++, or TypeScript is required.
  • Proven experience delivering backend APIs, especially GraphQL, and consuming them from a modern web stack is required.
  • Production experience with React, TypeScript, and modern CSS layout is required, including the judgment to build usable interfaces for complex workflows.
  • Experience building applications on cloud computing platforms such as AWS, Azure, or GCP and using container technologies such as Docker and Kubernetes is required.
  • Expert proficiency in SQL is required.
  • Demonstrated experience designing and operating distributed systems in production, including asynchronous workflows, queues, retries, idempotency, and partial failure, is required.
  • A track record of shipping and operating production services, including on-call ownership, is required.

Responsibilities

  • Build and own the agent execution runtime, including durable, resumable, long-running workflows with checkpointing, idempotent steps, cancellation, and step- and run-level timeouts.
  • Design and implement the agent tool layer, including a versioned registry, schema validation, per-tenant enablement, and server-side authorization.
  • Build the connector framework for third-party security control planes, including endpoint detection and response, firewalls, identity, security information and event management, and cloud identity and access management.
  • Implement the safe-change pipeline, including dry runs and simulation, blast-radius classification, approval gates for high-impact actions, staged rollout, rollback, and an immutable per-tenant audit trail.
  • Build the operator-facing front end in React and TypeScript, translating dense system state into interfaces users can understand and act on.
  • Build the client-side data and streaming layer that keeps interfaces accurate against long-running, incrementally updating state using WebSockets rather than polling.
  • Extend the tenant-isolation model to agents taking 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 ETL pipelines that turn pentest and remediation outcomes into datasets used by researchers to train and evaluate systems.
  • Instrument systems with distributed tracing across agent runs, per-tenant cost and token accounting, and tools to determine why an agent acted as it did.
  • Partner with AI researchers, attack engineers, and product teams to take capabilities from prototype to production and provide platform constraints to inform research direction.

Desired Qualifications

  • Experience building agentic or LLM-backed systems in production.
  • Experience with a durable execution or workflow engine such as Temporal, or experience building equivalent checkpointing.
  • Experience building multi-tenant platforms with hard isolation requirements, workload identity, and short-lived credential brokering.
  • Experience integrating many third-party APIs behind a normalized abstraction.
  • Familiarity with security control planes and their APIs, including endpoint detection and response tools such as CrowdStrike, SentinelOne, and Microsoft Defender; firewalls; security information and event management; and cloud identity and access management.
  • Experience with relational databases such as PostgreSQL and graph databases such as Neo4j, and experience building GraphQL backends.
  • Experience with client-side data and streaming patterns such as React Query or Apollo, GraphQL subscriptions, and WebSockets for long-running, incrementally updating state.
  • Experience building operator-facing or admin interfaces where density, auditability, and safe handling of destructive actions matter more than visual polish.
  • Experience with observability tools such as Datadog, Prometheus, or Grafana, and distributed tracing.
  • Awareness of prompt injection and untrusted-input handling in systems where an agent consumes data from its operating environment.

About the Company

Horizon3.ai

Autonomous pentesting SaaS for vulnerabilities

Horizon3.ai specializes in cybersecurity by offering NodeZero, a SaaS platform for autonomous penetration testing. It lets enterprises simulate cyber-attacks on their own systems in a self-service way, without installing persistent agents, and without ongoing human intervention. The platform works by running security-focused attack simulations in production environments to uncover exploitable vulnerabilities and weak controls, delivering vulnerability assessments, threat simulations, and compliance-oriented testing through tiered subscription plans. This approach differentiates Horizon3.ai from traditional pentesting by being self-service, agentless, and safe to run in live environments, while targeting enterprise customers that must meet standards such as PCI DSS. The company aims to help organizations improve their security posture, prioritize remediation, and maintain regulatory compliance by continuously identifying and fixing weaknesses.

Company size
501-1,000
Company stage
Series E
Total funding
$437M
Headquarters
San Francisco, CA
Founded
2019

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