AI Deployment Engineer, Cyber
About the team The AI Deployment Engineering team is responsible for helping developers and enterprises safely and effectively deploy OpenAI technologies in production. We act as trusted technical advisors and thought partners for customers, working side by side with their teams to identify high-value use cases, design
What this role actually needs.
About the team The AI Deployment Engineering team is responsible for helping developers and enterprises safely and effectively deploy OpenAI technologies in production. We act as trusted technical advisors and thought partners for customers, working side by side with their teams to identify high-value use cases, design 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 AppSec, DevSecOps, vulnerability management, SOC/IR, detection engineering, red team, cloud security, identity, and GRC automation use cases. - 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 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 CISO-level outcomes and practitioner-level implementation details so each audience understands value, risk, and practical next steps. Requirements: - 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 CISO-level outcomes and practitioner-level implementation details so each audience understands value, risk, and practical next steps. - Create reusable field assets such as demo narratives, playbooks, FAQs, objection handling, qualification guides, assessment templates, and competitive positioning. - Validate, synthesize, and deliver high-signal feedback to Product, Engineering, Research, Security, and GTM teams based on recurring customer requirements, blockers, product gaps, and emerging cyber workflows. - Have 5+ years of technical consulting, solutions engineering, security architecture, cyber advisory, deployment engineering, professional services, or equivalent customer-facing technical experience. - Bring 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. Company context: OpenAI builds frontier AI systems, research infrastructure, and applied products for developers, enterprises, and global users.
Day-to-day expectations
OpenAI lists these responsibilities for the AI Deployment Engineer, Cyber role.
- 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 AppSec, DevSecOps, vulnerability management, SOC/IR, detection engineering, red team, cloud security, identity, and GRC automation use cases.
- 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 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 CISO-level outcomes and practitioner-level implementation details so each audience understands value, risk, and practical next steps.
What a strong candidate brings
These requirements are extracted from the source listing and normalized for UpJobz readers.
- 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 CISO-level outcomes and practitioner-level implementation details so each audience understands value, risk, and practical next steps.
- Create reusable field assets such as demo narratives, playbooks, FAQs, objection handling, qualification guides, assessment templates, and competitive positioning.
- Validate, synthesize, and deliver high-signal feedback to Product, Engineering, Research, Security, and GTM teams based on recurring customer requirements, blockers, product gaps, and emerging cyber workflows.
- Have 5+ years of technical consulting, solutions engineering, security architecture, cyber advisory, deployment engineering, professional services, or equivalent customer-facing technical experience.
- Bring 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.
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AI Deployment Engineer, Cyber is framed against UpJobz source checks, country scope, compensation visibility, and work-authorization signals so candidates can make a faster go/no-go decision.
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Current extracted signal: United States residents. UpJobz treats this as a search signal, not legal advice, and links visa-sensitive roles back to the relevant visa hub where possible.
Location read
Hybrid roles in San Francisco should be compared against commute, local salary bands, and nearby employer demand.
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Source: jobs.ashbyhq.com · Source ID: b46ffd99-f9f2-440c-ac13-448eb7911ad6 · Confidence: 97/100 · Last checked: Aug 15, 2026
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