Applied AI Engineer, Cyber
Remote • San Francisco • FullTime
Posted 2mo ago
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
Applied AI Engineer
About the job
OpenAI is seeking a Cybersecurity Applied AI Engineer to partner with customers and help them apply OpenAI models, APIs, Codex, and agentic workflows to real cybersecurity use cases. This customer-facing technical role requires the ability to move fluidly between executive strategy, practitioner-level cyber depth, and hands-on solution design. You will work with CISOs, security executives, application security leaders, SOC teams, security engineering teams, and hands-on practitioners to identify where AI can create measurable security outcomes and help customers evaluate and deploy workflows such as secure code review, vulnerability triage, threat modeling, remediation, SOC and incident response workflows, detection engineering, cloud security, GRC automation, and security validation. You will collaborate closely with Sales, Solutions Engineering, Product, Engineering, Research, and Security to turn customer needs into safe deployment patterns, reusable field assets, and product feedback.
Responsibilities
- Serve as the technical lead for AI-enabled cybersecurity workflows, partnering with security executives and technical practitioners.
- Lead discovery across various cybersecurity domains including AppSec, DevSecOps, vulnerability management, SOC/IR, detection engineering, red team, cloud security, identity, and GRC automation.
- Build and deliver customer-facing demos, prototypes, workshops, proofs of concept, and reference architectures using OpenAI APIs, Codex, agents, and common security tools.
- Scope pilots with clear success criteria, data requirements, workflow integrations, evaluation methods, security constraints, safety boundaries, and human approval points.
- Advise customers on safe implementation patterns, including tool and function calling, structured outputs, retrieval, sandboxing, data handling, guardrails, telemetry, auditability, and approval-gated side effects.
- Translate between executive-level outcomes and practitioner-level implementation details.
- Create reusable field assets such as demo narratives, playbooks, FAQs, and qualification guides.
- Deliver high-signal feedback to Product, Engineering, Research, Security, and GTM teams based on customer requirements and product gaps.
Requirements
- 5+ years of technical consulting, solutions engineering, security architecture, cyber advisory, deployment engineering, professional services, or equivalent customer-facing technical experience.
- Strong cybersecurity domain expertise across one or more areas such as application security, cloud security, identity, vulnerability management, secure SDLC, incident response, detection engineering, threat intelligence, red teaming, or security architecture.
- Ability to communicate credibly with CISOs, CTOs, security executives, engineering leaders, and highly technical security practitioners.
- Hands-on experience building prototypes or production systems with APIs, Python or JavaScript, agents, scripts, CLIs, GitHub workflows, CI/CD systems, logs, tickets, scanners, or other common security tooling.
- Understanding of how to design AI workflows with retrieval, structured outputs, tool use, evals, guardrails, telemetry, sandboxing, and human-in-the-loop review.
- Comfort in scoping pilots from ambiguous customer pain, including success metrics, required data, workflow integrations, evaluation criteria, deployment assumptions, and decision gates.
- Evidence-first security judgment: validate findings, separate true positives from noise, document assumptions, and avoid overstating model or security claims.
- Ability to own problems end-to-end, operate with high throughput across multiple concurrent customer projects, and know when to stay hands-on versus create reusable leverage.
- Humble attitude, eagerness to help colleagues, and a desire to ensure team and customer success.
Benefits
- Relocation support to new employees