Staff Security Engineer, AI-Driven Detection

About Fullscript

We're an industry-leading health technology company on a mission to help people get better. We started in 2011 with one simple idea. Make it easier for practitioners to access the products they trust so they can deliver better care.

That simple idea grew into a platform that powers every part of care. Today, more than 125,000 practitioners use Fullscript for clinical insights, lab interpretations, patient analytics, education, and access to high-quality supplements. Over 10 million patients rely on Fullscript to stay connected to their care plans and follow through on treatment.

We build tools that make care smarter and more human. Tools that save time, simplify decisions, and help practitioners stay closely connected to the people they care for. When everything they need is in one place, they can focus on what matters most: helping people get better.

This is your invitation

Bring your ideas, your grit, and your care for people.

Join us and shape the future of care.

The Opportunity

We're looking for a Staff Security Engineer to define and drive Fullscript's defensive threat detection, incident response, and AI-assisted SecOps capability across our cloud infrastructure, identity, endpoints, and application ecosystems.

This role sits at the technical core of our Security function. You will architect modern detection systems, leverage AI/ML to automate SecOps workflows, and establish defensive testing practices for AI threat vectors. Partnering with Engineering and Platform teams, you will ensure our detection and response capabilities scale with Fullscript's fast-growing, AI-first infrastructure.

The ideal candidate has owned enterprise-scale detection engineering and incident response end-to-end. You are a pragmatic, forward-thinking engineer who excels at designing AI-augmented SOC workflows, conducting targeted AI defensive testing, and converting threat telemetry into automated, high-precision detection and response systems.

What You’ll Do

Detection Engineering & Defensive Strategy

• Set the multi-quarter technical direction for detection and response, and drive it across Security, Platform, and Engineering teams.
• Architect, author, and maintain advanced detection logic across SIEM, cloud infrastructure, identity systems, endpoint protection, and AI/ML pipelines.
• Establish detection coverage and defensive controls against emerging AI and agentic threat vectors (e.g., prompt injection, tool misuse, and data exfiltration patterns).
• Own the full rule lifecycle, from authoring and testing through tuning and retirement, and measure it against concrete signals: detection coverage, precision (false-positive rate), and time-to-detect.
• Create and maintain dashboards and reporting that give leadership visibility into alert volume, response times, and trends over time.

AI-Augmented Security Operations & Automation

• Design and deploy AI-assisted investigation workflows that leverage LLMs and automated agents to accelerate triage, context enrichment, and threat containment.
• Build and extend internal security tooling to support identity resolution, cross-source log correlation, and natural-language querying over security telemetry.
• Automate the handoff between detection tooling and our ticketing system so investigations move from alert to resolution with minimal manual work.

Incident Response & Investigations

• Lead and support security investigations end-to-end, from initial triage through containment and resolution.
• Mentor Security Operations team members and set the standards the team builds against, including rule quality, detection-as-code practices, and investigation rigor.
• Partner with relevant teams across the business to investigate and remediate security escalations surfaced from Customer Support, Customer Delivery, and internal teams.
• Maintain and improve response playbooks based on lessons learned from real investigations.
• Participate in an on-call rotation to respond to security incidents outside business hours.

AI Defensive Testing & Validation

• Threat model new and existing systems, including AI agents and services, to identify what could go wrong, what we would need to see to catch it, and how we would respond.
• Lead defensive testing, purple-teaming, and adversarial validation exercises to test alert fidelity and evaluate detection resilience against AI-driven threats.
• Partner with Platform and Engineering teams to ensure new AI services and features expose necessary logging and telemetry for effective security monitoring.
• Evaluate authorization and access-control changes for security-relevant blast radius, and drive remediation with the e