Applied AI Engineer – Cybersecurity (Tokyo)

About the role

We are looking for 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 works with CISOs, security executives, and practitioners to design and deploy AI‑enabled security workflows.

Key responsibilities

• Deeply embed with strategic customers as the technical lead for AI‑enabled cybersecurity workflows, serving as a trusted partner to both security executives and technical practitioners.
• Lead discovery across application security, DevSecOps, vulnerability management, SOC/IR, detection engineering, red teaming, cloud security, identity, and GRC automation use cases.
• Build and deliver demos, prototypes, workshops, proofs of concept, and reference architectures using OpenAI APIs, Codex, agents, scripts, CLIs, GitHub workflows, CI/CD systems, logs, tickets, scanners, and other 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.

Required profile

• 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 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.
• Evidence‑first security judgment: validate findings, separate true positives from noise, document assumptions, and avoid overstating model or security claims.

Required skills

• Python or JavaScript programming.
• Experience building prototypes or production systems with APIs, OpenAI APIs, Codex, agents, scripts, CLIs, GitHub workflows, CI/CD pipelines, logs, tickets, and scanners.
• Designing AI workflows with retrieval, structured outputs, tool use, evaluations, guardrails, telemetry, sandboxing, and human‑in‑the‑loop review.
• Scoping pilots from ambiguous customer pain, defining success metrics, data requirements, workflow integrations, evaluation criteria, deployment assumptions, and decision gates.