Staff Software Engineer (Malware Detection)

Chainguard

9d•$170,000 - $231,000•Remote

About The Position

Chainguard is building the most trusted source for open source software. Every artifact Chainguard distributes is evaluated by our scanner before it reaches a customer. It determines whether a package, container, or AI agent skill is safe to use and sits between our customers and compromised software. What began as a high-leverage internal system has become a core platform powering Chainguard Libraries, Containers, Agent Skills, and future products. We're hiring a Staff Software Engineer to lead the engineering of that platform. You'll own its architecture, scale, and reliability. You'll partner closely with Product Security to turn threat research into detections that run accurately and fast on every artifact we distribute, and with Product to define how customers experience a verdict. This is a backend and production-infrastructure role in a security domain, not a security research role. Product Security develops what the scanner looks for; you build and run the machinery that makes those detections fast, accurate, and dependable across every artifact we distribute. Deep detection-research experience is welcome, but it isn't what we're hiring for here.

Requirements

Multiple years building and operating production backend or infrastructure systems, with a clear track record of staff-level ownership and technical leadership.
Strong Go experience, or deep backend systems experience with the ability to ramp quickly in Go.
Experience owning highly technical platforms or backend infrastructure that supports multiple products or internal customers.
Experience with high-throughput, event-driven pipelines where throughput, latency, and correctness all matter at once.
Strong understanding of software supply chain security, malware detection, vulnerability management, or adjacent security domains.
Demonstrated success making engineering design and prioritization decisions in technically complex and ambiguous environments.
Comfort owning a metric like false-positive rate, instrumenting it honestly, and driving it down in a domain where a missed detection and a false alarm both carry real customer cost.
Experience deploying and operating services in production, with strong judgment around reliability, observability, and operational tradeoffs, and genuine comfort being on the hook when they misbehave.

Nice To Haves

Experience with malware detection, static analysis, software composition analysis (SCA), or vulnerability scanning.
Familiarity with package ecosystems such as npm, PyPI, Maven, Go modules, or container registries.
Experience building reusable platform capabilities that support multiple products.
Background in cloud infrastructure, software supply chain security, or enterprise security platforms.
Experience working with AI-assisted security analysis or automated threat detection systems, where output quality is measured and regression-tested rather than assumed.
Experience with sandboxing and dynamic analysis: eBPF, gVisor, seccomp, or container isolation.
Comfort working across application and infrastructure layers, including cloud infrastructure and infrastructure as code tools such as Terraform.

Responsibilities

Build the measurement behind coverage and precision: the pipelines, metrics, and dashboards the product is steered by.
Engineer the feedback loop between Engineering and Product Security so a detection change can be evaluated and shipped in hours, not days.
Build the systems for reviewing, escalating, and correcting detections quickly, including bulk correction at ecosystem scale.
Own the architecture of Chainguard's shared malware scanning platform: scan orchestration, verdict storage, and the APIs every consuming product depends on.
Scale the scanner beyond Libraries to Containers, Agent Skills, and future artifact types.
Make the tradeoffs between detection quality, performance, and extensibility concrete in throughput, latency, and cost.
Build and scale the analysis itself: deterministic static analysis alongside AI-assisted reasoning over artifact contents.
Partner with Product Security to take emerging-threat detections from research prototype to production, running on every new release across every ecosystem we cover.
Build the APIs and services behind how customers investigate, enforce, and appeal scanner findings.
Build the backend for policy management and enterprise-scale operations.
Operate the scanner as a system in the critical path of every customer install: alerting, queue health, verdict-before-serve guarantees, and incident response.
Mentoring engineers and raising the bar on design and code review.
Cross-functional collaboration skills with the ability to influence Product, Security, Design, and GTM partners.