Staff Software Engineer, Defensive Agent

Horizon3

3d•$229,000 - $270,000•Remote

About The Position

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. We are hiring a Staff Software Engineer to lead the technical work for NodeZero's defensive agents: the systems that translate proven attack paths into continuous actionable remediation. You'll set direction alongside our AI researchers, who define what the agents should reason about, and lead the engineers who build the platform underneath them. Over time this role owns the technical strategy for how autonomous remediation becomes a core NodeZero product capability rather than a set of recommendations in a report. This is a technical leadership role without direct people management. You lead through architecture, code, design review, and mentorship, not through performance reviews and headcount. It is also not a pure architect role. You will write production code every week, review PRs from the engineers you lead, and partner closely with Product to sequence the right problems in the right order. You will be the person who both draws the system diagram on the whiteboard and commits the first slice of it to main.

Requirements

Bachelor's Degree in Computer Science, Computer Engineering or related field.
7+ yrs professional software engineering experience using modern object-oriented or functional languages (Python, Go, Scala, C++, TypeScript, etc).
Experience building applications on cloud computing platforms such as AWS, Azure, GCP, using container technologies such as Docker and Kubernetes.
Deep experience with agentic or LLM-backed systems in production with a clear-eyed view of where they fail and how to contain it.
Expert proficiency in SQL.
Demonstrated experience designing and operating distributed systems in production: asynchronous workflows, queues, retries, idempotency, and partial failure.
A track record of shipping and operating production services, including on-call ownership.

Nice To Haves

Experience with a durable execution (such as Temporal) or workflow engine or having built equivalent checkpointing yourself.
Experience building multi-tenant platforms with hard isolation requirements, workload identity, and short-lived credential brokering.
Experience integrating a long tail of third-party APIs behind a normalized abstraction.
Familiarity with security control planes and their APIs — EDR (CrowdStrike, SentinelOne, Microsoft Defender), firewalls, SIEM, cloud IAM.
Experience with database architectures including relational (PostgreSQL) and graph (Neo4j), and experience building GraphQL backends.

Responsibilities

Owns the end-to-end technical vision for the workstream and rallies the team around it — from blank doc through shipping, iterating, and deprecating.
Production code contributions at Lead/Staff level in a modern backend language (Python, Go, Rust, or similar) in a service-oriented environment.
Sets and raises the technical bar (design reviews, code quality, operational discipline) by example rather than by mandate.
Mentors and enhances the engineers around them; builds the frameworks and architecture for others to do the best work of their careers.
Holds the team accountable to outcomes rather than activity; surfaces risks and tradeoffs early and in writing.
Serves as the durable technical interface between AI research and platform engineering, so research direction accounts for platform constraints early rather than at handoff.
Translates ambiguous product goals into concrete technical roadmaps.
Makes build vs. buy vs. integrate calls with business context, not just engineering preference — including which model providers, orchestration frameworks, and control-plane integrations we own versus adopt.
Partners closely with PM — comfortable in PRD reviews, not just sprint planning.
Sequences an MVP without painting the team into a corner.
Designs durable execution for long-running, resumable agent runs.
Designs the tool and authorization layer so tenant scope and permissions are enforced by the systems the agent calls.
Owns multi-tenant isolation for agents that take write actions.
Architects the connector framework over heterogeneous third-party security control APIs.
Treats untrusted environment data as an attack surface; understands prompt injection and keeps model output out of the path that authorizes privileged action.
Builds observability that makes agent behavior explainable.