New opportunity

Applied AI Engineer, Codex

OpenAI · Singapore

About this role

The Applied AI Engineering (Codex) team at OpenAI is seeking a technically deep, creativity-driven Applied AI Engineer to help customers adopt OpenAI's coding tools throughout their software development lifecycle. You will act as a trusted technical partner, guiding engineering teams as they integrate Codex into their projects and workflows. This role is based in Singapore and requires a hybrid work model of 3 days in the office per week. Relocation assistance is available.

Responsibilities

Serve as the primary technical subject matter expert on OpenAI Codex for a portfolio of customers.
Partner with customers to design and implement AI-enhanced development workflows, from rapid prototyping to scalable production rollout.
Build high-quality demos, reference implementations, and workflow automations, often using Codex in the development process.
Lead large-format workshops, technical deep dives, and hands-on enablement sessions.
Contribute technical content, examples, and best practices to the OpenAI Cookbook.
Gather product insights from customer deployments to inform product proposals and model feedback.
Influence customer strategy regarding SDLC, technical roadmaps, and organizational workflows.

Requirements

Ability to speak Mandarin is a requirement for working with Mandarin-speaking customers and vendors.
5+ years of experience in technical consulting, post-sales engineering, solutions architecture, or similar customer-facing roles.
Active power user of AI coding tools with a deep understanding of developer productivity.
Experience building demos, integrations, and prototypes.
Proven ability to deliver high-impact workshops or technical training to engineering teams.
Strong communication skills for explaining complex technical concepts.
Experience contributing technical guides or patterns publicly.
Passion for customer success, reliability, and operational excellence.

For full details about this role, click “Apply on company site” to view the employer’s original posting.

Skills for this role

AI coding toolsTechnical consultingSolutions architecturePost-sales engineeringMandarinPrototypingTechnical workshopsSoftware development lifecycleCodex

Checking your profile…

Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.

Understand the role

What matters most

Technical Enablement and Adoption
The core priority is driving the successful integration of Codex into customer software development lifecycles. This requires moving beyond simple product demonstrations to designing and implementing scalable, AI-enhanced workflows that provide measurable improvements in developer productivity.
Customer-Facing Technical Leadership
Acting as a trusted advisor, you must influence customer strategy and technical roadmaps. This involves leading high-impact workshops and deep dives to educate engineering teams on best practices, security, and operational readiness when deploying AI coding tools.
Product Feedback Loop
You are expected to act as a bridge between the field and product teams. By gathering high-fidelity insights from real-world deployments, you will inform product proposals and model feedback, directly shaping the future direction of Codex.
Content Creation and Community Impact
Contributing to the OpenAI Cookbook is a key requirement. You must be able to translate complex technical patterns into clear, pedagogical guides and reference implementations that help the broader developer community adopt AI tools effectively.

Likely challenges to think through

Navigating Ambiguity in Rapidly Evolving AI
The AI landscape changes quickly, and customer needs are often ill-defined. Prepare by demonstrating your ability to iterate on novel solutions in ambiguous environments, focusing on how you maintain technical rigor while experimenting with emerging AI capabilities.
Balancing Technical Depth with Strategic Communication
You must explain complex technical concepts to both hands-on builders and engineering leaders. Prepare by practicing how to frame technical architectural decisions in the context of business strategy and organizational SDLC goals.
Managing Diverse Stakeholder Expectations
The role requires cross-functional collaboration with Sales, Product, and Engineering. Prepare by highlighting experiences where you successfully aligned disparate internal and external stakeholders toward a unified technical implementation plan.

Practice your answers

Technical practice

Integrating AI Coding Tools into SDLC

What to coverExplain how you would advise an engineering team to integrate AI coding tools into their existing software development lifecycle. Focus on balancing developer productivity with code quality, security, and the necessity of human oversight.

Prototyping and Workflow Automation

What to coverDescribe your process for building a high-signal demo or integration using AI coding tools. Discuss how you use these tools to accelerate your own development process while ensuring the final output is reliable and scalable.

Technical Workshop Facilitation

What to coverHow do you structure a technical deep-dive or hands-on enablement session for engineering teams? Address how you ensure the session is outcomes-driven and effectively communicates complex AI concepts to diverse technical audiences.

Gathering and Translating Product Insights

What to coverWhen working with customers, how do you distinguish between specific user feedback and broader product requirements? Provide an approach for translating these insights into actionable model feedback or product proposals for internal engineering teams.

AI Coding Tool Power User Experience

What to coverAs a power user of AI coding tools, what specific customizations or patterns have you implemented in your own workflow to maximize productivity? Explain your perspective on what makes an AI-enhanced developer workflow truly effective.

Addressing Security and Operational Readiness

What to coverWhen advising a customer on adopting AI coding tools, how do you address concerns regarding security, data privacy, and operational readiness? Discuss the trade-offs between rapid adoption and maintaining enterprise-grade safety standards.

Contributing to Technical Documentation

What to coverDescribe your approach to creating technical guides or patterns for a public audience, such as the OpenAI Cookbook. Focus on how you balance technical depth with clarity and pedagogy to ensure the content is accessible and impactful.

Managing Ambiguity in AI Deployments

What to coverHow do you approach a customer project where the requirements are ambiguous or the technology is rapidly evolving? Explain your strategy for iterating toward a solution while maintaining a trusted advisor relationship.

Behavioural practice

Influencing Customer Strategy

What to coverDescribe a situation where you had to influence a customer's technical roadmap or organizational workflow. Use the STAR method to explain how you framed your recommendation, addressed resistance, and achieved a successful outcome.

Handling Complex Technical Communication

What to coverProvide an example of a time you had to explain a highly complex technical concept to a non-technical or mixed-level audience. How did you tailor your communication to ensure clarity and persuade the stakeholders?

Cross-Functional Collaboration

What to coverDescribe a project where you worked closely with Sales, Product, and Engineering teams to deliver a solution. How did you manage competing priorities and ensure the customer's needs were effectively advocated for?

Commitment to Customer Success

What to coverShare an example of a time you went above and beyond to ensure a customer's success with a new technology. What specific actions did you take, and how did you measure the impact of your support?

Sharpen your knowledge

Topics to prepare

AI-Enhanced Software Development Lifecycle (SDLC)
Understand how AI coding tools integrate into various stages of the SDLC, from initial planning and rapid prototyping to production deployment and maintenance. Review how to frame these tools as strategic assets for engineering leaders to improve developer productivity and operational excellence.
Technical Consulting and Customer Enablement
Study frameworks for effective technical consulting, focusing on how to act as a trusted advisor. This includes identifying customer pain points, managing technical roadmaps, and translating complex AI capabilities into actionable business value for engineering teams.

Skills to revise

Technical Workshop Facilitation
Practice designing and delivering high-impact, hands-on technical workshops. Focus on creating engaging content that teaches engineering teams how to use AI tools effectively and safely, ensuring the sessions are outcomes-driven and tailored to different technical skill levels.
Prototyping and Demo Development
Develop your ability to build scrappy, high-signal prototypes and reference implementations. Practice using AI coding tools to accelerate your own development process, ensuring your demos clearly articulate the value and capabilities of the technology to potential customers.
Technical Writing for Developer Communities
Refine your ability to contribute clear, pedagogical technical guides and patterns. Practice documenting best practices for AI tool adoption in a way that is accessible to the broader developer community, similar to content found in the OpenAI Cookbook.
Mandarin Language Proficiency
Ensure you are prepared to conduct technical discussions, workshops, and vendor communications in Mandarin, as this is an explicit requirement for supporting Mandarin-speaking customers and partners in the Singapore region.

Your preparation checklist

Document your AI-driven development workflow
Prepare a detailed walkthrough of how you currently use AI coding tools to accelerate your own software development. Highlight specific customizations, prompt engineering patterns, and productivity gains you have achieved to demonstrate your status as a power user.
Create a portfolio of technical demos and prototypes
Assemble a collection of high-signal demos or integrations you have built. Ensure these examples showcase your ability to use AI tools to solve real-world engineering problems and illustrate how you can translate complex requirements into functional, scalable code.
Prepare a technical workshop outline
Draft a plan for a hands-on enablement session designed for engineering teams. Focus on how you would teach developers to adopt AI coding tools safely and effectively, emphasizing outcomes-driven pedagogy and your ability to explain complex technical concepts clearly.
Refine your Mandarin communication for technical contexts
Since Mandarin proficiency is a requirement for this role, prepare to discuss technical architecture, SDLC strategies, and product feedback in Mandarin. Practice explaining complex AI concepts to ensure you can effectively support Mandarin-speaking customers and vendors.
Develop strategic questions for the interview
Prepare thoughtful questions regarding the current challenges engineering teams face when integrating AI, the typical lifecycle of a Codex deployment, and how the team balances operational excellence with rapid prototyping to better understand the role's impact.

Availability last checked: 18 Oct 2026. Status can change after a check; confirm on the employer’s website. Report an issue · Our checking policy

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