Applied AI Engineer

About the role

OpenAI's Applied AI Engineering team turns frontier AI capabilities into safe, reliable, high-impact production systems, working with customer executives, product and engineering teams, security leaders and transformation teams. As an Applied AI Engineer you will partner with leading organizations to design, build and deploy AI systems that deliver measurable business outcomes, moving from use-case selection and architecture through prototyping, evaluation, production launch and scale. The role is based in Sydney, Australia, with a hybrid model of 3 days in the office per week and relocation assistance for new employees.

Key responsibilities

• Partner with enterprise customers to identify high-value opportunities and turn them into technical architectures, implementation plans, evaluation strategies and success criteria.
• Design, build and deploy AI systems that solve important customer problems and produce measurable results.
• Write and debug code to build prototypes, evaluation harnesses, reference implementations, integrations and production accelerators.
• Make technical decisions across models, agents, retrieval, tools, data, reliability, observability, latency, cost, safety, security and governance.
• Diagnose complex implementation challenges, reproduce failures, test hypotheses and drive blockers to resolution.
• Help customers move from prototypes to reliable production systems and sustained adoption.
• Work with customer engineering teams and OpenAI Product, Research, Engineering, Security and go-to-market teams to turn deployment experience into product feedback.
• Create reusable architectures, tooling, playbooks and technical guidance for future enterprise deployments.

Required profile

• Demonstrated track record of designing, building and delivering AI or machine-learning systems in enterprise environments, from prototype to production.
• Substantial personal contributions in code, architecture, evaluation, debugging or production engineering, beyond program or stakeholder management.
• Ability to connect technical decisions to customer workflows, adoption and measurable business outcomes.
• Clear communication with engineers, technical leaders, security teams, product leaders and executives.
• High agency, strong technical judgment and end-to-end ownership in ambiguous environments.

Required skills

• Highly proficient in Python; experience with JavaScript, TypeScript or another relevant language is valuable.
• Understanding of systematic AI system evaluation using representative data, graders, production signals and human judgment.
• Experience with enterprise production requirements such as integrations, reliability, observability, security, privacy, data governance, performance and cost.