Staff Detection Engineer

Staff Detection Engineer For It

Fluidstack operates the compute infrastructure powering frontier AI. The work running on it is among the most consequential being done today, and the adversaries interested in it are among the most sophisticated, persistent, and well-resourced anywhere. We are building Detection & Response Engineering from the ground up: engineering-led, agent-first, and built to scale across IT, OT, and physical surfaces. As the Staff Detection Engineer for IT, you lead detection engineering for Fluidstack's IT surface. You set the standards that every detection engineer who follows inherits, and lay the foundations of detection on some of the most critical infrastructure being built today.

What you'll do

• Lead detection engineering for Fluidstack's IT surface, including cross-domain detections where IT bridges OT or physical surfaces.
• Author and tune production detections as code, with peer review, CI/CD, and measured precision and recall.
• Apply AI and machine learning to build effective detections, including behavioral analytics and anomaly detection at scale.
• Develop novel detection tooling, including agentic capabilities that use LLMs for triage, investigation, and response.
• Set the engineering standards, coverage methodology, and quality metrics for the detection engineering discipline.
• Conduct threat and security research that informs detection logic, surfaces coverage gaps, and drives new detections.
• Partner with security platform engineers, incident response, and threat intelligence to close the detection-to-response loop.
• Participate in the on-call rotation for incident response.

About you

• You have strong detection engineering experience and have built detection programs at scale.
• You are fluent across coding and querying languages, pick up new ones quickly, and have handled security-relevant data at massive scale and complexity.
• You have written sophisticated detection logic against diverse telemetry, not synthesized it from vendor templates.
• You have handled security incidents and investigated anomalies as part of a team.
• You have set up detection CI/CD, or know how you would build it on day one.
• You have well-founded opinions on what makes a detection program work in production.
• You read the agent-first thesis as the most interesting design choice in security operations right now.
• You have built or contributed to internal tooling, not just consumed commercial products.
• You see what is needed, scope it yourself, and run with it.

Strong candidates may also have

• Experience building or operating agentic detection tooling using LLMs.
• Experience designing and tuning LLM-based triage or investigation systems against measured precision and recall.
• Experience with Python and SQL applied to detection development and security data analysis.
• Experience at the boundary between detection engineering and security platform engineering at scale.
• Background in detection or security engineering at GPU compute, HPC, or other hyperscale infrastructure.

Salary & benefits

• Competitive total compensation package (salary + equity)
• Retirement or pension plan, in line with local norms
• Health, dental, and vision insurance
• Generous PTO policy, in line with local norms

The base salary range for this position is $250,000 - $330,000 per year, depending on experience, skills, qualifications, and location. This range represents our good faith estimate of the compensation for this role at the time of posting. Total compensation may also include equity in the form of stock options.

We are committed to pay equity and transparency.

Fluidstack is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans' status, or any other characteristic protected by law. Fluidstack will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.