Operations Finance Process and Technology Expert at Apple

Austin, Texas, United States -

Full Time

Start Date

Immediate

Expiry Date

14 Sep, 26

Salary

0.0

Posted On

16 Jun, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Process Optimization, AI/ML Implementation, Supply Chain Finance, Technical Program Management, SQL, Python, GenAI, System Architecture, Data Visualization, Prompt Engineering, Agile/Scrum, API Integration, Data Pipelines, MLOps, Agentic AI, Cross-functional Leadership

Industry

Computers and Electronics Manufacturing

Description

Apple’s Finance Transformation Org is seeking an experienced and highly motivated Operations Finance Process and Technology Expert to lead the strategic development, implementation, and optimization of technology solutions supporting our global operations finance processes. As a process and technology expert, you’ll understand the finance processes and systems supporting Apple’s operations, supply-chain and logistics functions, re-engineer, optimize and build new generationtechnology solutions that will power Apple's Operations finance functions into the future, ensuring high standards of technical quality, development rigor, and delivery accountability. This role sits at the heart of a major transformation model to drive strategic outcomes at Apple's scale. DESCRIPTION This role will be critical in driving process optimization, efficiency, scalability, and innovation across the finance org supporting Engineering, Operations, Supply-Chain, AppleCare and logistics functions. The role will drive end-to-end delivery of complex, cross-functional AI/ML and Ops finance programs by owning technical solution roadmaps, milestones, and execution across engineering, product, and business teams to ensure on-time, high-quality launches. You'll dive deep into technical designs, data, and system architecture, infrastructure and Cloud based solutions alongside engineers and data scientists, leveraging their knowledge of software engineering, GenAI, MLOps, and agentic AI to unblock issues, manage risks, and make informed prioritization trade-offs. They align diverse stakeholders through clear communication, data-driven decision-making, and structured executive narratives continuously improving processes to increase velocity and translate technical complexity into measurable business impact. The ideal candidate will possess an understanding of supply-chain and operations business processes, enterprise-level technology platforms, and have a proven track record of delivering complex technology projects with an emphasis on Process Innovation & Artificial Intelligence and Machine Learning. You will create an environment where the right technology - whether data pipelines, AI-powered automation, or custom tooling-is applied to the right problem to drive scalable, well-architected outcomes. You'll work closely with the Ops Finance Transformation Lead, Operations Finance leaders, and technology partners including FDT, ETS and IS&T. MINIMUM QUALIFICATIONS Masters degree in Supply-Chain, Finance, Computer Science, Engineering, Analytics, or equivalent technical field and 8+ years of technical/engineering program management experience OR Bachelor’s in Supply-Chain, Computer Science, Engineering, Analytics, or equivalent technical field with 10+ years experience Previous experience with software engineering, GenAI, Machine Learning, AI, and supply chain/operations domains Dive deep into data, technical designs, and root-cause analysis to resolve complex challenges with high analytical rigor Proficiency with data acquisition tools advanced SQL, Python, data visualization, and analytics platforms Familiarity with agentic AI frameworks, tool-use patterns (e.g., MCP servers, function calling, skills), and the ability to evaluate how autonomous agents and multi agent network can be applied to program and operational workflows Knowledge of large language models (LLMs) and prompt engineering techniques — sufficient to partner effectively with software engineers and data scientists on GenAI-powered solutions Experience managing feature roadmaps across interconnected systems, with the ability to stitch together finance and supply chain concepts (e.g., fulfillment, logistics, demand planning) into cohesive program strategies Familiarity with software engineering best practices including testing frameworks, code quality standards, secure development practices, system architecture, strong understanding of APIs, data architecture, and system integration enabling effective partnership with software engineering teams on technical deliverables PREFERRED QUALIFICATIONS Operate effectively in ambiguous environments, demonstrating strong ownership, bias for action, sound judgment, and a commitment to delivering results with experience working in Agile/Scrum environments High intellectual curiosity to learn and understand business needs, with the ability to provide in-depth evaluations of complex engineering and analytic issues Proactively identify cross-team dependencies, risks, and trade-offs; implement mitigation plans to ensure predictable, high-quality delivery Communicate effectively with senior leadership through structured written narratives and executive-ready program updates that translate technical complexity into business impact Inquisitive mindset with a desire for continued self-improvement and development of new skills Proven ability to work outside own area of expertise, perform business discovery, simplify and define the problem statement, extract key information, and propose potential analytic approaches Meticulous attention to detail and data integrity when managing program metrics and deliverables Drives organizational success by orchestrating & aligning X-functional teams toward shared goals Track record of staying current with industry best practices and rapidly adopting emerging technologies and methodologies

Responsibilities

Lead the strategic development and optimization of technology solutions for global operations finance, supply chain, and logistics processes. Drive the end-to-end delivery of complex AI/ML programs and technical roadmaps to increase operational efficiency and scalability.