Detection and Response Engineer

About Us:
AI needs a new infrastructure layer. We're building it at Modal.
Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now.
Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale.
We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September.
Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.

The Role:
We're looking for a Detection & Response Engineer to build the systems that help us identify, investigate, and respond to threats across our platform.
This is an engineering role focused on automation. You'll build detections, investigation tooling, and response capabilities that scale with our infrastructure, using AI where it meaningfully improves signal, investigation speed, and operational effectiveness.
You'll work closely with infrastructure, platform, and security engineers to ensure every incident makes the platform more resilient.

What You'll Work On:
Detection Engineering
Design and build high-fidelity detections for attacks, abuse, and anomalous behavior across our infrastructure and production systems

Continuously improve detections based on telemetry, threat intelligence, and lessons learned from incidents

Improve visibility across cloud infrastructure, containers, identity systems, and production services

Incident Response
Lead or participate in investigations spanning production infrastructure, cloud environments, and internal systems

Build playbooks and automation that reduce investigation time and improve response consistency

Drive post-incident improvements that eliminate entire classes of future incidents

Security Tooling & Automation
Build internal tooling that improves detection, investigation, and response workflows

Leverage LLMs to automate repetitive analysis, accelerate investigations, and surface actionable insights from security telemetry

Improve the collection, quality, and usability of security telemetry across the platform

Engineering Partnership
Partner with engineering teams to ensure new systems are observable and secure by default

Help teams instrument services with the telemetry needed for effective detection and response

Drive security improvements that make the platform easier to defend over time

What We're Looking For:
Experience in detection engineering, incident response, security engineering, or software engineering with a strong security focus

Strong software engineering skills with experience building production systems

Experience investigating security incidents in cloud-native or distributed environments

Familiarity with modern cloud infrastructure, Kubernetes, Linux, and networking

Experience building detections using logs, telemetry, behavioral signals, or large-scale event data

Strong SQL skills for investigating security events and developing detections

Interest in applying AI and LLMs to detection, investigation, and response, including understanding emerging threats involving AI-powered systems

Strong written and verbal communication skills

Preferred Qualifications:
Experience building AI- or LLM-powered security tooling

Experience with SIEM, SOAR, or EDR platforms

Experience with Kubernetes security or large-scal