Staff Software Engineer - Detection Platform (GoLang)

Huntress is a cybersecurity company that builds technology backed by a human-led Security Operations Center to protect businesses from cyber threats. The Staff Software Engineer will lead modernization of detection engines and pipelines, improve reliability under load, and establish event schemas and data contracts while writing and reviewing production code.

Responsibilities:

• Detection engine and pipeline modernization. We're rewriting our detection engine to support the full Sigma v2 specification, including stateful correlation of patterns across many events over time. In parallel, we're reworking several existing detection pipelines and building new ones, moving off the bespoke per-product detectors we've accumulated and onto a common platform. You'll lead major workstreams across both and own the validation approach that proves a reworked pipeline still behaves like the one it replaces, so we can turn old paths off knowing we haven't lost anything
• Reliability and behavior under load. A detection pipeline that quietly stops producing signals is worse than one that crashes loudly, and detection volume spikes for reasons we don't always control. You'll build the guarantees that make quiet failure impossible: end-to-end latency measurement, liveness coverage, and alerting that fires when expected work stops arriving. You'll also build the mechanisms that keep a spike bounded and recoverable
• Event schemas and data contracts. Our schema and transformer layer are what several other engineering teams build their detections against. You'll help drive toward a coherent internal standard and build the validation and drift-detection tooling that catches upstream changes before they break detections

Requirements:

• Deep experience designing, building, and operating production distributed systems at scale, primarily in Go, with the range to work across several layers of the stack
• You have replaced or substantially re-architected a live, high-throughput system without breaking its consumers, and you can walk us through how you proved the new path was equivalent, staged the cut-over, and decided it was safe to retire the old one
• Experience with high-volume event or data pipelines, and a good feel for how they behave under load: where things queue, where they fall behind, and what happens to correctness when they do
• Strong operability instincts. You design observability in rather than retrofitting it, and you've built alerting that catches the absence of expected work, not just errors
• Demonstrated technical leadership across team boundaries. You've set a direction that other teams had to build against and raised the engineering bar around you, without needing positional authority
• Judgment about production quality: when a system is good enough to ship, when it needs more evaluation, and when it shouldn't ship at all
• Hands-on experience with AI coding tools, and a point of view on using them well, where correctness is a security outcome
• A background in security operations or security engineering: time spent writing or tuning detections, or working in a SOC. You know what makes a detection maintainable, how fast noise erodes a SOC's trust in its tooling, and why a missed detection is a different class of failure than a noisy one
• Experience with detection-as-code or other rule- and DSL-driven systems, including the parsing and evaluation work that supporting a specification properly entails
• Experience building platform tooling for non-engineer authors such as rule writers, analysts, and researchers, where the product surface is a language, an API, and a feedback loop
• Ruby on Rails experience. Some of our pipeline and application code is Rails, and you'll occasionally read and review Ruby. It's a nice-to-have, not a requirement; we'll help you ramp