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Security Engineer, Detection and Response

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Published
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25 Sep 2026Apply before
Opportunity details

About this role.

AI Summary

OpenAI is seeking a senior Security Engineer to build and operate detection and response capabilities protecting sensitive infrastructure, products, research environments, intellectual property, and customer data. The role centers on high-signal detection engineering, incident response automation, telemetry requirements, and measurable operational quality across endpoints, identity, SaaS, cloud, Kubernetes, and datacenter-adjacent systems. The engineer will partner with security and infrastructure teams to close visibility gaps, implement controls, and ensure new systems launch with threat models and response playbooks. This position also addresses emerging risks in a frontier AI environment, including detection and response for agents operating across systems at scale.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

5/5
EasyHard

Pace & Pressure

5/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightThis is a highly advanced security engineering role spanning cloud, containers, endpoint and identity telemetry, lower-level infrastructure, and incident response operations. It requires independent technical judgment, cross-functional influence, and the ability to design safe, measurable automation for novel AI-related threats.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job medianHighly competitive
$339,000
US market range$220k–$380k
AI insightThe disclosed yearly base compensation range is USD 293,000 to USD 385,000, producing an offer median of USD 339,000. The estimated US market range for a senior/staff-level detection and response security engineer is USD 220,000 to USD 380,000 yearly; the stated range is positioned at the upper end of the market, consistent with a high-impact frontier AI security role.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you design a detection engineering lifecycle for a new Kubernetes environment?

I would begin with a threat model and inventory of workloads, identities, control-plane components, network paths, and available telemetry. I would define priority adversary behaviors, implement detections with clear ownership and rollout safeguards, and measure coverage, precision, alert latency, and investigation outcomes. I would then establish tuning and review loops so detections evolve with the environment and observed attacker techniques.

Describe an automation you would build to reduce incident-response toil while maintaining safety.

I would automate repeatable enrichment and evidence collection first, such as retrieving identity history, endpoint activity, cloud audit events, and relevant Kubernetes context. Containment actions would be gated by confidence thresholds, approvals, or narrowly scoped reversible controls. Every workflow would produce auditable logs, preserve original evidence, and be evaluated against time-to-triage and false-action rates.

How do you translate adversary TTPs into practical detections?

I map the TTP to the systems and telemetry where the behavior can be observed, then identify signals that distinguish malicious activity from normal administration. I prioritize detections by potential impact, likelihood, and signal quality, validate them through controlled testing or historical data, and document associated investigation and response steps. Where direct detection is weak, I recommend instrumentation or control improvements rather than relying on low-confidence alerts.

What telemetry and controls would you request when a team is launching a new cloud service?

I would request an architecture and data-flow review covering identities, privileged actions, network exposure, data access, deployment paths, and third-party dependencies. Required telemetry would typically include cloud audit logs, identity events, application and API logs, network signals, asset inventory, and configuration changes. I would also define detection use cases, retention needs, ownership, escalation paths, and response playbooks before launch.

How would you approach detection and response for AI agents operating across infrastructure?

I would model agents as high-privilege or high-scale actors whose actions need strong identity attribution, authorization boundaries, and complete auditability. Detection would focus on abnormal tool use, unusual access patterns, policy bypass attempts, unexpected privilege changes, and high-impact action sequences. Response controls should support rapid revocation, scoped containment, evidence preservation, and measurable safeguards that minimize disruption to legitimate workloads.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.

About the Team

Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity.

The Security team protects OpenAI’s technology, people, and products. We are technical in what we build but are operational in how we do our work, and are committed to supporting all products and research at OpenAI. Our Security team tenets include: prioritizing for impact, enabling researchers, preparing for future transformative technologies, and engaging a robust security culture.

About the Role

As a Security Engineer on Detection & Response, you’ll help protect OpenAI’s most sensitive assets– including our intellectual property, customer data, and the infrastructure that supports them– by building and operating the systems we use to detect suspicious activity and respond effectively when it matters. You’ll work across endpoints, identity, cloud, hyperscale compute infrastructure, and datacenter-adjacent layers, partnering closely with security teams and infrastructure owners to define the telemetry and response requirements we need and building tooling and automation where it delivers the most leverage.

In this role, you will:

  • Build and evolve Detection & Response capabilities across OpenAI’s infrastructure, products, and research environments, with an emphasis on high-signal detection and reliable operational response.

  • Engineer detection pipelines and tooling: develop rule lifecycle management, measurement/quality loops (coverage, precision, latency), tuning processes, and safe rollout patterns.

  • Automate response and investigations by building workflows that reduce toil (triage, enrichment, containment, evidence capture) and improve time-to-understand/time-to-contain.

  • Partner with other Security teams and system/infrastructure owners across the company to ensure new systems ship with the right telemetry, threat models, and response playbooks from day one.

  • Define D&R requirements and drive visibility across endpoints, identity, SaaS, cloud, Kubernetes: identify telemetry/control gaps, prioritize them, and advocate for fixes with partner teams (and implement directly when it’s the fastest/most effective path).

  • Evaluate and respond to emergent security concerns in a frontier AI lab environment, such as detection and response strategies for agents operating across infrastructure at scale.

You might thrive in this role if you:

  • Have hands-on threat detection and/or incident response experience, including building detections, running investigations, and improving operational playbooks.

  • Understand modern adversary tradecraft (TTPs) and can translate it into practical detection strategies and response actions.

  • Bring a threat modeling mindset. You can evaluate new infrastructure or features, identify D&R implications (what could go wrong, what we’d need to see, how we’d respond), and turn that into concrete requirements for teams shipping the system.

  • Have experience working in Kubernetes/containerized environments, including building detections from cluster telemetry and understanding common failure and attack modes (workloads, nodes, control plane, networking).

  • Are comfortable reasoning about lower-level infrastructure and datacenter risks, such as firmware/BMC surfaces, network segmentation/telemetry, and hard-to-observe control paths.

  • Have experience across major cloud platforms (Azure, AWS, GCP, OCI), and can design cloud-agnostic detection approaches where possible.

  • Like building automation that replaces repetitive D&R work, including thoughtfully using agent-style workflows where they meaningfully reduce toil, while keeping outcomes measurable, auditable, and safe.

  • Are energized by new problem areas at a forward-leaning technology company: e.g., thinking through how to detect and respond to agents operating across systems at scale, and turning those ideas into pragmatic telemetry and response requirements.

  • Communicate clearly and collaborate well across teams. You can translate D&R needs into clear requirements, align stakeholders, and drive follow-through across technical and non-technical audiences.

  • Are comfortable with scripting and enjoy using AI/agent tooling to accelerate investigations and automation—more “directing” than doing everything by hand.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.

For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.

Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.

To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.

We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.

OpenAI Global Applicant Privacy Policy

At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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