Apple's Finance organisation is looking for experienced technical leaders to help us build the future. As Lead AI Engineer, you'll architect and deliver AI-powered solutions that transform how Finance operates globally-from automating complex workflows to enabling smarter decision-making at scale.
This is a builder-leader role where your code ships to production and your technical decisions shape our AI strategy. You'll work at the intersection of cutting-edge AI and enterprise finance, solving unique challenges around scale, compliance, and reliability that few engineers ever tackle.
You'll have the rare opportunity to define how AI transforms finance at one of the world's most innovative companies. Your work will directly impact how Apple operates financially, with the autonomy to choose the right technologies and the resources to build at scale. If you're passionate about applying AI to solve real business problems and want to lead a team that ships meaningful products, we want to hear from you.
Description
Build and Ship: Design and deliver production AI applications that Finance teams across Apple depend on daily-from RAG-powered analytics to agentic automation workflows
Set the Technical Bar: Define engineering standards for AI delivery, from LLM evaluation frameworks to production observability, ensuring we build systems that are auditable, scalable, and SOx-compliant
Lead by Example: Write code alongside your team, whether architecting a new service, optimizing a RAG pipeline, or debugging a production issue
Mentor and Elevate: Guide engineers in AI best practices, conduct architecture reviews, and build a culture of engineering excellence
Drive Production Excellence: Establish SLOs, implement drift monitoring, strengthen CI/CD pipelines, and ensure our AI systems meet Finance's rigorous operational standards
Partner and Deliver: Collaborate with Finance stakeholders to identify high-impact opportunities, prototype solutions rapidly, and ship features that deliver measurable value
Preferred Qualifications
LLMOps expertise: evaluation pipelines, prompt versioning, drift detection
Experience with agentic frameworks (LangChain, LangGraph, Google ADK)
Understanding of finance fundamentals (SOx compliance, P&L, financial reporting cycles)
Background in ML algorithms and their practical applications in enterprise settings
Minimum Qualifications
7+ years shipping production web applications with demonstrated technical leadership
Graduate degree in CS, Software Engineering, or related field (or equivalent experience)
Deep expertise in Python and modern JavaScript/TypeScript frameworks (React, Vue)
Proven track record deploying generative AI solutions (RAG, prompt engineering, evaluation frameworks) to production
Strong Kubernetes and cloud platform experience (AWS, GCP, or Azure)
Excellence in system design, code review, testing strategies, and GitOps practices
Experience mentoring engineers and driving technical decisions across teams
Ability to communicate complex technical concepts to both engineering and finance audiences
