Staff Security Engineer - Detection and Response

Ridgeline•Reno, NV

4h•$205,000 - $256,000•Onsite

About The Position

As a member of the Detections and Response Team (DART) at Ridgeline, you will bring your expertise and new ideas to help develop and execute our Detections and Response roadmap. Acting as a significant architect for the systems overseeing our critical infrastructure - both within AWS and across our broader technical landscape - you will apply your expertise to elevate our collective detection coverage and lead the response to our highest-impact security events. Additionally, in this AI-forward role, you will engineer and validate robust, AI-augmented detection and response pipelines while serving as a key point person to ensure our standards for responsible and fluent AI usage remain relevant and effective. At Ridgeline, the workplace culture is just as important as the products we build. We value ownership, transparency, and a bias toward action - which means we’re always looking for solutions rather than just identifying problems. We’re a team that chooses growth over comfort, owns our setbacks as much as our wins, and thrives on the kind of collaboration that pushes everyone to do their best work. If that’s the environment where you do your best work, we would be interested to meet you.

Requirements

8+ years working in detection, security operations, incident response, or software engineering, with a proven track record of leading cross-functional technical initiatives.
Advanced proficiency in Python (preferred) or another high-level language like Kotlin or TypeScript.
Demonstrated skill engineering AI/LLM-driven systems: it is essential you are capable of building augmented detection, triage, and investigation workflows and rigorously validating their output for correctness and risk.
Expertise authoring detections mapped to attacker TTPs (e.g., MITRE ATT&CK).
Extensive background building and operating detection-as-code and alerting pipelines, tuned for signal quality and noise reduction.
Strong command of the AWS ecosystem, specifically across logging and telemetry (CloudTrail, VPC Flow Logs, GuardDuty, CloudWatch), investigative tools (Athena, IAM analysis), and compute (Lambda, ECS/EKS).
Fluency with infrastructure-as-code (e.g., Terraform) and CI/CD practices.
Strong written and verbal communication skills, with the ability to explain detection and response decisions clearly to engineers, product partners, and stakeholders.

Nice To Haves

History leading complex, high-impact incidents as a technical lead or incident commander.
Hands-on design of AI agents or LLM-based automation in a security operations context.
Contributions to open source detection/security tooling or published security research.

Responsibilities

Shape the DART roadmap based on business priorities and threat models, proactively identifying detection requirements during the design phase of new features and infrastructure.
Eliminate detection gaps by performing variant analysis to close entire classes of vulnerabilities rather than addressing individual findings.
Architect AI-powered detection and triage pipelines that maintain accuracy and reduce manual effort, minimizing false positives so every alert warrants a response.
Collaborate as a key architect for our SIEM, SOAR, and adjacent security platforms, designing scalable, resilient ingestion, enrichment, and alerting frameworks.
Own the technical architecture and maturity of our incident response program, guiding the response to complex high-impact events, interfacing with leadership during major incidents, and driving findings to systemic remediation.
Set the technical direction for DART-owned codebases and infrastructure, making sound architectural tradeoffs that balance speed, correctness, and maintainability.
Establish team standards for the effective and responsible use of AI in detection and response workflows, including appropriate human-in-the-loop guardrails.
Influence security strategy across engineering organizations, building consensus with Staff+ engineers through technical credibility instead of unilateral directives.
Elevate the team's technical expertise by mentoring junior and mid-level engineers through code reviews, collaborative problem solving, and knowledge sharing.