Bachelor's degree or equivalent experience in computer science, engineering, or similar.
Proficiency in Python or Rust for building data pipelines and internal tools.
Experience responding to real security incidents in production environments.
Hands-on experience building and operating security data pipelines at scale.
Strong understanding of cloud environments (AWS, GCP, Azure) and Kubernetes.
Familiarity with host and network forensics, including endpoint telemetry and network logs.
Clear communication skills for incident reports and intel briefs.
Responsibilities
Lead end-to-end incident response: triage, containment, eradication, and recovery.
Design and operate security data pipelines for telemetry collection and normalization.
Author and maintain high-fidelity detections across various security tools.
Build and run a threat intelligence practice focused on AI-related threats.
Proactively hunt for threats and develop automation for response tooling.
Collaborate with teams to detect AI-specific threats in production environments.
Participate in an on-call pager rotation for security incidents.
Benefits
Generous health, dental, and vision benefits.
Unlimited PTO.
Paid parental leave.
Relocation support as needed.
Full Job Description
About the Role
We're looking for a detection and response engineer to build how we find, investigate, and stop threats against our company, platforms, models, and data. You'll own the pipelines that turn raw telemetry into high-fidelity detections, lead the response when real incidents happen, and run a threat intelligence practice that keeps our defenses focused on the adversaries who actually target frontier AI labs. You'll partner closely with security, infrastructure, research, and product teams so that detection and response scale with the company instead of slowing it down.
What You'll Do
Lead incident response end-to-end: triage, scoping, containment, eradication, recovery, and blameless postmortems that turn lessons into new detections and controls.
Design, build, and operate the security data pipelines and tooling that power detection and response: collecting, normalizing, enriching, and storing telemetry from cloud, Kubernetes, identity, endpoint, SaaS, and application sources.
Author, deploy, and maintain high-fidelity detections across SIEM, endpoint, cloud, and security tooling
Build and run our threat intelligence practice: track actors and campaigns relevant to AI labs such as espionage, model weight theft, supply chain compromise, and credential abuse. Turn that intel into hunts, detections, and hardening recommendations.
Proactively hunt for threats across our environment, and build automation and response tooling: enrichment, playbooks, automated containment that shortens time to detect and respond.
Collaborate with researchers and product teams to detect AI-specific threats in production.Develop and exercise incident response plans, on-call processes, and tabletop exercises with engineering, research, legal, and leadership.
Participate in an on-call pager rotation for security incidents.
Skills and Qualifications Minimum qualifications
Bachelor's degree or equivalent experience in computer science, engineering, or similar.
Proficiency in Python or Rust for building data pipelines, detections, and internal tools.
A track record responding to real security incidents in production environments, including leading investigations and coordinating across teams under pressure.
Hands-on experience building and operating security data pipelines at scale: log ingestion, parsing and normalization, enrichment, and storage and query in a SIEM or data lake (e.g., Splunk, Elastic, Panther, BigQuery, Snowflake, or ClickHouse).
Experience producing and consuming threat intelligence: tracking adversary TTPs, mapping them to frameworks like MITRE ATT&CK, and translating intel into detections and hunts.
Strong understanding of cloud, AWS, GCP, or Azure, Kubernetes, and identity provider telemetry, and how attackers move through these environments.
Familiarity with host and network forensics, including endpoint telemetry, memory and disk analysis, and network logs.
Comfort operating across the stack and owning projects end-to-end.
Clear communication: incident reports, intel briefs, and postmortems for both technical and non-technical audiences.
Preferred qualifications
Detection and response experience at an AI lab, cloud provider, or other high-threat environment targeted by sophisticated actors.
Experience detecting AI-specific abuse, such as prompt injection, model extraction, or anomalous API usage.
Familiarity with ML infrastructure telemetry: GPU clusters, training jobs, and model artifact storage.
Experience with stream processing (e.g., Kafka, Flink, Vector) and cost-aware log management at high volume.
Malware analysis or reverse engineering experience.
Talks, blogs, open-source detection content, or published threat research.
Logistics
Location: This role is based in San Francisco, California.
Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $300,000 - $350,000 USD.
Visa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together.
Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.
