Applied AI Engineer, Cyber

About the role

The Applied AI Engineering team helps developers and enterprises safely deploy OpenAI technologies. In this customer‑facing role you will partner with security leaders to design and implement AI‑enabled cybersecurity workflows that deliver measurable outcomes.

Key responsibilities

• Embed with strategic customers as the technical lead for AI‑driven security use cases, spanning AppSec, DevSecOps, SOC/IR, detection engineering, cloud security, identity, and GRC automation.
• Design, prototype, and deliver demos, workshops, proofs of concept, and reference architectures using OpenAI APIs, Codex, agents, scripts, CLIs, GitHub workflows, and CI/CD pipelines.
• Scope pilots with clear success criteria, data requirements, workflow integrations, evaluation methods, safety boundaries, and human‑approval points.
• Advise on safe implementation patterns, including tool and function calling, structured outputs, retrieval, sandboxing, guardrails, telemetry, and auditability.
• Create reusable field assets such as demo narratives, playbooks, FAQs, qualification guides, and assessment templates.
• Provide high‑signal feedback to Product, Engineering, Research, Security, and GTM teams based on recurring customer needs and product gaps.

Required profile

• 5+ years of technical consulting, solutions engineering, security architecture, or equivalent customer‑facing technical experience.
• Deep cybersecurity expertise in at least one area (application security, cloud security, identity, vulnerability management, incident response, detection engineering, threat intelligence, red teaming, or security architecture).
• Proven ability to communicate credibly with CISOs, CTOs, security executives, and highly technical practitioners.
• Hands‑on experience building prototypes or production systems with APIs, Python or JavaScript, agents, scripts, CLIs, GitHub workflows, CI/CD systems, logs, tickets, or scanners.
• Strong judgment for evidence‑first security, validating findings, separating true positives from noise, and documenting assumptions.

Required skills

• Python
• JavaScript
• OpenAI APIs and Codex
• GitHub workflows
• CI/CD systems
• Command‑line interfaces (CLI)
• Security tooling (scanners, log analysis, ticketing systems)
• Design of AI workflows with retrieval, structured outputs, tool use, guardrails, and human‑in‑the‑loop review