Applied AI Engineer, Codex

The Applied AI Engineering team helps enterprises put Codex to work on their most important engineering workflows, working alongside customer engineers to turn frontier AI capabilities into systems that improve how software is built, shipped, secured, and operated. The team's work spans unfamiliar codebases, legacy systems, data pipelines, infrastructure, and enterprise integrations. The engineer will work directly with technical leaders and engineers to identify opportunities and take them from discovery through implementation and evaluation, combining hands-on software engineering, architecture, and technical leadership to make Codex part of how customers get important work done. Working with product, engineering, research, and account teams, the engineer turns deployment experience into evidence that informs improvements to Codex. The position is based in Sydney, Australia, with three office days each week.

Responsibilities

Lead customer engineering engagements from workflow discovery and architecture through implementation, evaluation, and handoff, with clear customer owners, delivery milestones, and measurable success criteria; Assess customer repositories, data systems, infrastructure, security controls, and development practices to understand constraints, determine readiness, and identify where Codex can have the greatest impact; Build and validate workflows alongside customer engineers, developing integrations, tool gateways, evaluation harnesses, reference implementations, and automations, often using Codex in your own development process; Establish baselines, quality and security guardrails, and evaluation methods that demonstrate whether a workflow is reliable, useful, and ready to expand; Turn customer engagements into reusable tools, architectures, and deployment patterns, and translate recurring challenges into actionable feedback for product, engineering, and research teams; Document technical decisions and results for handoff and reuse, establishing clear customer, partner, or delivery-team ownership for production release, ongoing operation, and maintenance; Use evidence to recommend when to expand a workflow, redirect an engagement, or stop work when value or feasibility cannot be demonstrated

Requirements

5+ 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 have a clear perspective on how agents can automate complete workflows; Bring technical depth in one or more areas, such as software engineering, data systems, cloud infrastructure, or enterprise integrations, and enjoy learning across disciplines; Understand how software is tested, released, and operated, and can reason about the security, reliability, and access requirements of enterprise environments; Can turn an ambiguous customer problem into a practical technical plan with credible estimates, measurable acceptance criteria, and clear tradeoffs; Communicate effectively with technical leaders and hands-on engineers, collaborate through uncertainty, and turn individual customer work into solutions others can reuse

Benefits

Relocation assistance is available to new employees