About this role
Enterprises struggle to integrate Codex into complex engineering workflows across unfamiliar codebases, legacy systems, and data pipelines. The Applied AI Engineering team solves this challenge by helping organizations turn frontier artificial intelligence capabilities into operational systems that improve software development, security, and infrastructure.
In this role, the engineer works directly with technical leaders to identify high-value opportunities, build solutions from discovery through implementation, and establish reliable measurement criteria. Daily tasks include assessing customer repositories, developing integration tools, building evaluation harnesses, and translating deployment experiences into feedback for internal product and research teams.
Candidates who succeed here typically combine software development expertise with consulting skills and a practical understanding of enterprise environments. Someone who enjoys untangling ambiguous technical problems, building alongside customers, and using AI tools in their own development process will thrive in this position.
What you will do
- Lead customer engineering engagements from workflow discovery and architecture through implementation, evaluation, and handoff.
- Assess customer repositories, data systems, infrastructure, security controls, and development practices to determine readiness.
- Build integrations, tool gateways, evaluation harnesses, reference implementations, and automations alongside customer engineers.
- Establish baselines, quality and security guardrails, and evaluation methods to demonstrate workflow reliability.
- Turn customer engagements into reusable tools, architectures, and deployment patterns.
- Document technical decisions and results for handoff and reuse while establishing clear ownership.
- Use evidence to recommend when to expand a workflow, redirect an engagement, or stop work when feasibility cannot be demonstrated.
What you need
- Have five or more years of relevant experience in software development, deployment engineering, data or infrastructure engineering, technical consulting, or solutions architecture.
- Can build, debug, and evaluate production-relevant software and quickly understand unfamiliar systems.
- Actively use AI coding tools, have adapted them to your own work, and possess a clear perspective on agent workflows.
- Bring technical depth in areas such as software engineering, data systems, cloud infrastructure, or enterprise integrations.
- Understand how software is tested, released, and operated, and reason about security, reliability, and access requirements.
- Can turn an ambiguous customer problem into a practical technical plan with credible estimates and acceptance criteria.
- Communicate effectively with technical leaders and hands-on engineers while collaborating through uncertainty.
Benefits
- Relocation assistance is available to new employees
Skills and tech stack
Questions candidates ask
What is the remote work or office policy?
The position is based in Sydney, Australia, with three office days each week. Relocation assistance is available to new employees.
What will I actually work on day-to-day?
You will work directly with technical leaders and engineers to identify valuable opportunities and take them from discovery through implementation and evaluation. Tasks might include building a Codex-assisted release review workflow, modernizing a legacy data pipeline, or connecting an agent to production incident investigation systems.
Who will I collaborate with across the organization?
You will work alongside customer engineers and collaborate with product, engineering, research, and account teams. This involves turning deployment experience into evidence that informs improvements to Codex.