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Lead AI Engineer, Finance Digital Transformation

Apple
Posted 4 days ago, valid for 23 days
Location

Cupertino, CA, US

Salary

Competitive

Contract type

Full Time

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Sonic Summary

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  • Apple's Finance organization is seeking a Lead AI Engineer with a minimum of 7 years of experience in shipping production web applications and a graduate degree in a related field.
  • In this role, you will architect and deliver AI-powered solutions that enhance Finance operations globally, focusing on automating workflows and enabling smarter decision-making.
  • You will set engineering standards for AI delivery, ensuring the systems are auditable, scalable, and compliant with regulations like SOx.
  • The position requires deep expertise in Python, modern JavaScript/TypeScript frameworks, and experience with deploying generative AI solutions in production environments.
  • While the salary is not explicitly mentioned, the role offers a unique opportunity to influence how AI transforms finance at one of the world's leading companies.
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. Yourwork 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.

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

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


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