AI Solution Architect I

Job Summary

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. Partner with senior business stakeholders to understand their pre-sales needs, guide their AI strategy, and identify the highest value use cases and applications. Work with business and technical teams to demonstrate the value of our solutions and recommend architectural patterns to kickstart their implementation and development. 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. Help customers evaluate OpenAI for workflows like secure code review, vulnerability triage, threat modeling, remediation, SOC workflows, detection engineering, and security validation.

Key Responsibilities

• 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.

Skill Requirements

• 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 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.

Other Requirements

• Familiarity with OpenAI’s models, APIs, Codex, Codex Security, Daybreak, or related cyber capabilities.
• Experience working with security-product companies, global systems integrators, or cybersecurity partners.
• Depth across application security, cloud security, identity, secure SDLC, vulnerability management, detection and response, or attacker tradecraft.
• Experience developing repeatable field assets, technical enablement, or product feedback mechanisms across multiple regions.

Preferred Qualifications

• Master’s degree in computer science, Artificial Intelligence, Data Science, Engineering, or a related field, or relevant cloud, AI, security, architecture, or data certifications.
• Experience with Azure, AWS, or Google Cloud; enterprise data platforms; vector databases and search; API management; containers and Kubernetes; DevSecOps; and MLOps/LLMOps toolchains.
• Experience in consultative or presales solutioning, regulated-industry environments, architecture governance, and creation of reusable reference architectures, accelerators, evaluation suites, and bid-response artifacts.