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Horizon3.ai

Autonomous pentesting SaaS for vulnerabilities

Staff Backend Engineer - Internal

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

About the Job

Requirements

  • Own multiple complex initiatives, make sound prioritization decisions, and keep work moving across teams with competing dependencies.
  • Set direction, make progress through ambiguity, deliver independently while bringing others along, and communicate what is and is not yet guaranteed.
  • Design distributed work for retries, partial failure, and recovery, and diagnose asynchronous systems and production issues methodically.
  • Weigh performance, correctness, scalability, operability, maintainability, and explain tradeoffs and their customer or business impact.
  • Influence technical decisions beyond the immediate team and build alignment across engineering and product partners.
  • Develop other engineers through mentorship, thoughtful reviews, and clear technical guidance.
  • Produce strong technical writing for architecture proposals, design documents, runbooks, and API documentation.
  • Bachelor's degree in Computer Science, Computer Engineering, or a related field.
  • At least 8 years of professional software engineering experience using modern object-oriented or functional languages such as Python, Java, Go, Scala, C++, or TypeScript.
  • Demonstrated technical leadership on high-complexity backend or data-platform initiatives, including setting direction and delivering across multiple teams or stakeholders.
  • Experience designing, building, and operating production data-processing, ETL, or distributed task-processing systems at scale.
  • Hands-on experience with backend APIs, relational data models, and SQL in production systems.
  • Experience building applications on cloud platforms such as AWS, Azure, or GCP, and using container technologies such as Docker.

Responsibilities

  • Set architecture and technical direction for core Python services and APIs, designing for correctness, performance, maintainability, and long-term evolution.
  • Lead complex backend initiatives from problem definition and design through delivery and production operation, coordinating dependencies across attack, frontend, data, and other engineering teams.
  • Design and evolve reliable processing workflows for large-scale, long-running internal assessments and data workloads, including scheduling, retries, idempotency, state management, and failure recovery.
  • Shape processing and data-access patterns to scale across concurrent workloads, with clear visibility into progress, failures, and throughput.
  • Lead the design and operation of high-throughput ETL pipelines that transform attack-team knowledge-graph output into reliable, queryable relational datasets for the customer portal.
  • Guide the attack-path data model and presentation layer so identity, privilege-escalation, and lateral-movement paths are represented accurately and consistently in customer results.
  • Read and optimize raw SQL; untangle unfamiliar queries, identify performance and correctness risks, and guide safe production optimization or refactoring.
  • Define and evolve GraphQL and graph-based API patterns that let product components and customers explore complex relationships in internal attack data.
  • Own the operational health of backend systems in the domain and establish and promote practices for observability, uptime, scalability, release readiness, and on-call response.
  • Drive system architecture decisions across team boundaries, make tradeoffs explicit, and write design documents that provide shared direction and reusable technical reference.
  • Serve as a technical leader in cross-functional planning, align backend investments with product priorities, and communicate risks, dependencies, and options to technical and non-technical stakeholders.
  • Mentor and unblock engineers through design discussions, code reviews, and technical guidance; raise engineering standards and help others take on broader ownership.
  • Partner with frontend engineers, product managers, and designers to turn backend capabilities into a clear, responsive user experience and ensure attack paths and assessment data are presented clearly.

Desired Qualifications

  • Deep experience shaping cross-team backend architecture and establishing practices that improve system quality, reliability, or operability beyond the immediate team.
  • Ability to analyze and rewrite slow SQL queries to substantially improve runtime, with repeated experience establishing this as a routine team practice.
  • Experience building ETL that runs unattended against messy real-world source data without silently dropping records or stalling without alerts, and handling highly uneven per-tenant scale.
  • Comfort connecting backend, frontend, and data pipelines and establishing patterns for how they meet.
  • Fluency with the team's modern Python toolchain, including SQLAlchemy, versioned migrations, uv, ruff, mypy, and pytest, and an inclination to raise those standards.
  • Experience designing durable, observable data workflows with orchestration engines such as Temporal, Prefect, Airflow, Celery, or similar.
  • Deep experience with GraphQL backends and graph databases such as Neo4j.
  • Experience owning observability for shipped systems, including metrics, alerting, and dashboards using tools such as Datadog, Prometheus, or OpenTelemetry, and raising operational standards for others.
  • Systems engineering experience with attack-path data, relational datasets, and services that make complex security results useful to customers.
  • Experience deploying containerized services, including in Kubernetes-based production environments.
  • Experience building platform capabilities or internal tooling that multiple engineering teams rely on.
  • Experience in cybersecurity or with internal attack, identity, privilege-escalation, and vulnerability data, and enough offensive-security context to collaborate fluently with attack engineers.

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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