Applied AI Engineer, Codex

Responsibilities

• Partner with engineering leaders and developers to identify high-value opportunities for Codex and translate them into architectures, implementation plans, evaluation strategies, and success criteria.
• Design, build, and deploy AI-powered software development workflows for planning, coding, testing, review, debugging, and delivery.
• Build prototypes, evaluation harnesses, reference implementations, integrations, workflow automations, and production accelerators.
• Help customers move experiments into reliable production workflows, sustained adoption, and scaled impact.
• Design evaluations for AI coding systems using representative software engineering tasks, automated graders, production signals, and developer feedback.
• Make technical decisions across models, agents, tools, developer environments, reliability, observability, latency, cost, safety, security, and operational readiness.
• Diagnose implementation challenges, reproduce failures, test hypotheses, and resolve technical blockers.
• Lead technical deep dives, workshops, and hands-on enablement for advanced AI coding workflows.
• Translate deployment insights into product proposals, model feedback, and technical requirements.
• Create reusable architectures, tools, examples, guides, and technical patterns for future deployments.
• Advise technical leaders on AI coding systems, software development lifecycle changes, engineering practices, and organizational workflows.

Requirements

• Demonstrated experience designing, building, and delivering software or AI systems in enterprise environments from prototype through production.
• Significant hands-on contributions to code, architecture, evaluation, debugging, integrations, or production engineering.
• High proficiency in Python and familiarity with modern software development environments.
• Experience or strong interest in AI coding tools and improving developer productivity.
• Ability to evaluate AI coding systems systematically through representative tasks, automated evaluations, production signals, and developer feedback.
• Experience with enterprise production requirements including developer-tooling integrations, reliability, observability, security, privacy, data governance, performance, and cost.
• Ability to connect technical decisions to developer workflows, adoption, engineering productivity, and measurable business outcomes.
• Strong communication across engineers, engineering leaders, security teams, product leaders, and executives.
• Comfortable leading technical workshops and hands-on adoption sessions.
• High agency, strong technical judgment, and end-to-end ownership in ambiguous environments.
• Fluency in Japanese and English.

Nice-to-haves

• Experience with JavaScript, TypeScript, or another relevant programming language.
• Background in applied AI or machine learning engineering, forward-deployed engineering, software engineering, developer tooling, customer engineering, solutions architecture, or technical consulting.
• Experience creating integrations, automations, production solutions, or reusable technical resources.

Compensation and Benefits

• Hybrid work model with three days per week in the office.
• Relocation assistance is available.