Applied AI Engineer
Salary not listed • Sydney, Australia • Full-time
Posted 9d ago
Job Location
Sydney, Australia
Also open in Singapore
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Engineer
About the job
OpenAI's Applied AI Engineering team partners directly with leading organizations to design, build, and deploy AI systems that deliver measurable business outcomes. This role involves combining deep technical judgment, hands-on engineering, and customer leadership to take ambitious ideas from use-case selection and architecture through prototyping, evaluation, production launch, and scale. You will write and debug code, build evaluation systems, resolve complex integrations, and guide decisions involving model behavior, reliability, latency, cost, safety, security, governance, and operational readiness. Success is measured by production systems, sustained adoption, and meaningful customer impact. This is a rare opportunity to work on consequential real-world deployments at the frontier of AI while directly influencing how OpenAI’s products evolve.
Responsibilities
- Partner directly with enterprise customers to identify high-value opportunities and translate them into technical architectures, implementation plans, evaluation strategies, and measurable success criteria.
- Design, build, and deploy AI systems that solve important customer problems and produce measurable business outcomes.
- Work hands-on in code to build prototypes, evaluation harnesses, reference implementations, integrations, and production accelerators.
- Make sound 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 toward resolution.
- Help customers progress from promising prototypes to reliable production systems, sustained adoption, and scaled impact.
- Partner closely with customer engineering teams and OpenAI Product, Research, Engineering, Security, and go-to-market teams, translating deployment experience into high-signal product feedback.
- Create reusable architectures, tooling, playbooks, and technical guidance that accelerate future enterprise deployments.
Requirements
- Demonstrated track record of designing, building, and delivering AI or machine-learning systems in enterprise environments, including taking systems from prototype to production.
- Substantial personal contributions in code, architecture, evaluation, debugging, or production engineering.
- High proficiency in Python and comfortable working across an AI application stack.
- Experience with JavaScript, TypeScript, or another relevant language is valuable.
- Understand how to evaluate AI systems systematically using representative data, graders, production signals, and human judgment.
- Experience navigating enterprise production requirements such as integrations, reliability, observability, security, privacy, data governance, performance, and cost.
- Ability to connect technical decisions to customer workflows, adoption, and measurable business outcomes.
- Communicate with clarity and credibility across hands-on engineers, technical leaders, security teams, product leaders, and executives.
- High agency, strong technical judgment, and end-to-end ownership in ambiguous environments.
- Ability to learn quickly, challenge assumptions constructively, and collaborate with humility.
Benefits
- Relocation assistance to new employees