Applied AI Engineer, Cyber

Responsibilities

• Serve as the technical lead for AI-enabled cybersecurity workflows for strategic customers.
• Lead discovery across application security, DevSecOps, vulnerability management, SOC and incident response, detection engineering, red teaming, 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, scripts, CLIs, GitHub workflows, CI/CD systems, logs, tickets, scanners, and security tools.
• Scope pilots with success criteria, data requirements, integrations, evaluation methods, security constraints, safety boundaries, and human approval points.
• Advise 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 CISO-level outcomes and practitioner-level implementation details.
• Create reusable field assets such as playbooks, FAQs, qualification guides, assessment templates, and competitive positioning.
• Deliver customer feedback to Product, Engineering, Research, Security, and go-to-market teams.

Requirements

• 5+ years of technical consulting, solutions engineering, security architecture, cyber advisory, deployment engineering, professional services, or equivalent customer-facing technical experience.
• Strong cybersecurity expertise in one or more areas including application security, cloud security, identity, vulnerability management, secure SDLC, incident response, detection engineering, threat intelligence, red teaming, or security architecture.
• Ability to communicate with CISOs, CTOs, security executives, engineering leaders, and 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 security tooling.
• Understanding of retrieval, structured outputs, tool use, evaluations, guardrails, telemetry, sandboxing, and human-in-the-loop review.
• Ability to scope pilots from ambiguous customer needs, including metrics, data, integrations, evaluation criteria, deployment assumptions, and decision gates.
• Evidence-first security judgment and the ability to validate findings, distinguish true positives from noise, document assumptions, and avoid overstating claims.
• Ability to own problems end-to-end across concurrent customer projects and create reusable leverage.
• Humble, collaborative attitude and willingness to support colleagues and customers.