Field Security Specialist (Cyber Security Solutions Engineer)

About the Team The Solutions Engineering team is made up of trusted technical advisors who help organizations adopt OpenAI’s technology safely, effectively, and responsibly. We partner closely with customers, Sales, Product, Engineering, and Security to translate frontier AI capabilities into practical workflows that create real-world impact. Cybersecurity is one of the most urgent areas where AI can help. As frontier models become more capable at reasoning over code, logs, infrastructure, and security evidence, organizations need guidance on how to evaluate, validate, and deploy these systems safely. Our goal is to help customers move from identifying risks to implementing solutions. About the Role We are committed to bringing together people from diverse backgrounds and perspectives who are excited to help build and deploy safe, useful AI. We are seeking a solutions engineer to partner with our Enterprise customers and ensure they achieve tangible business value from our models through the OpenAI suite of products. You will partner with senior business stakeholders to understand their pre-sales needs, guide their AI strategy, and identify the highest value use cases and applications. You will work with business and technical teams to demonstrate the value of our solutions and recommend architectural patterns to kickstart their implementation and development. You will work closely with Enterprise Sales, Security, and Product teams. We are looking for a Field Security Specialist to help security leaders and hands-on practitioners understand how OpenAI models, APIs, Codex, and agentic workflows can be applied to real cybersecurity use cases. This is a customer-facing specialist role for someone who can move fluidly between CISO-level conversations, practitioner-level technical depth, and hands-on solution design. You’ll help customers evaluate OpenAI for workflows like secure code review, vulnerability triage, threat modeling, remediation, SOC workflows, detection engineering, and security validation. You will be the field’s cyber expert: shaping discovery, demos, pilots, reference architectures, implementation guidance, and repeatable assets that help customers adopt AI safely in high-stakes security environments. In this role, you will: - Lead cyber workflow discovery with customers across AppSec, DevSecOps, vulnerability management, SOC/IR, detection engineering, red team, cloud security, and GRC automation. - Build and deliver customer-facing demos, workshops, proofs of concept, and reference architectures for AI-enabled security workflows. - Scope pilots with clear success criteria, data requirements, integrations, evaluation methods, safety boundaries, and human approval points. - Advise customers on safe implementation patterns, including tool/function calling, structured outputs, sandboxing, data handling, guardrails, auditability, and approval-gated side effects. - Translate between executive buyers and hands-on security practitioners, helping each audience understand 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. - Bring recurring customer requirements, product gaps, blockers, and high-value cyber workflows back to Product, Engineering, Security, and GTM teams. You might thrive in this role if you: - Have deep practitioner credibility across cybersecurity domains such as application security, cloud security, identity, vulnerability management, secure SDLC, incident response, detection engineering, or attacker tradecraft. - Have worked in a customer-facing, advisory, consulting, solutions engineering, security architecture, or technical field role. - Can build credible demos or prototypes using APIs, Codex, agents, scripts, CLIs, GitHub workflows, CI/CD systems, logs, tickets, scanners, or other common security tooling. - Understand how to design AI workflows with retrieval, structured outputs, tool use, evals, guardrails, telemetry, and human-in-the-loop review. - Are comfortable scoping pilots from ambiguous customer pain, including success metrics, required data, workflow integrations, evaluation criteria, deployment assumptions, and decision gates. - Communicate clearly with both CISOs and hands-on practitioners. - Have strong evidence-first judgment: you validate findings, separate true positives from noise, document assumptions, and avoid overstating claims. - Are excited to build leverage for the broader field by turning one-off customer work into repeatable assets and product feedback loops. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and hum

Deep practitioner credibility across cybersecurity domains such as application security, cloud security, identity, vulnerability management, secure SDLC, incident response, detection engineering, or attacker tradecraft. Experience in a customer-facing, advisory, consulting, solutions engineering, security architecture, or technical field role. Ability to build credible demos or prototypes using APIs, Codex, agents, scripts, CLIs, GitHub workflows, CI/CD systems, logs, tickets, scanners, or other common security tooling. Understanding of designing AI workflows with retrieval, structured outputs, tool use, evals, guardrails, telemetry, and human-in-the-loop review. Comfortable scoping pilots from ambiguous customer pain, including success metrics, required data, workflow integrations, evaluation criteria, deployment assumptions, and decision gates. Strong communication with both CISOs and hands-on practitioners. Evidence-first judgment to validate findings, differentiate true positives from noise, document assumptions, and avoid overstating claims. Motivation to build repeatable field assets and product feedback loops from one-off customer work.