Engineering Manager - Foundations, Finance Data & Technology

Apple Inc.
Austin, TX, United States
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Working hours
Regular working hours
Job source

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Application Frameworks Cloud Computing Cloud Engineering Data as a Services Distributed Systems Graph Database IT Management Open Source Technology Software Engineering Retrieval-Augmented Generation
+2 more
Information Technology Data Management

Job description

Imagine what you could do here. At Apple, new ideas quickly become platforms and capabilities that shape how the company operates at global scale. Bring passion, technical depth, and strong leadership, and there’s no limit to the impact you can have. The Finance Data and Technology (FDT) organization is seeking a Senior Engineering Manager to lead our Foundations team - the engineering force multiplier for every business-facing product and delivery pod across Finance. This team builds the shared platforms, frameworks, data services, and AI capabilities that let other teams move fast without sacrificing security, scale, or reliability., In this role, you will own the strategy, architecture, and execution of enterprise platforms spanning cloud infrastructure, data, application frameworks, and AI. You will bring proven, hands-on experience taking agentic AI systems from prototype to production, ideally in a finance or highly regulated setting, and you will use that experience to set the standard for how Finance adopts AI responsibly and at scale. You will operate at executive altitude, partnering closely with Enterprise IT (IS&T), security, privacy, and business-facing engineering leaders to align investment and priorities. You will lead with clarity, operate comfortably in ambiguity, and build a team that treats reusable platforms, not one-off projects, as the default way of working.

Requirements

10+ years of software engineering experience

3+ years leading managers and senior technical leaders across multiple teams

Bachelors degree in Computer Science, Statistics, Engineering, or equivalent practical experience

Preferred Qualifications

12+ years of software engineering experience, with 6+ years leading managers and senior technical leaders across multiple teams.

Background supporting Finance, Corporate Systems, Enterprise Analytics, or high-throughput data platforms.

Experience building developer platforms used by hundreds of engineers in large, complex enterprise environments.

Contributions to open-source platform tooling or enterprise AI frameworks.

Direct, hands-on experience designing and shipping an agentic AI solution into production - able to speak concretely to the architecture, evaluation approach, guardrails, and business outcome; finance or other regulated-industry deployment strongly preferred.

Working knowledge of agent orchestration, RAG/semantic retrieval, knowledge graphs, prompt and evaluation frameworks, and model governance sufficient to review designs and make build-vs-buy calls.

Deep expertise in cloud-native architectures, distributed systems, APIs, and modern data platforms at scale.

Track record building and operating large-scale platform engineering organizations used by hundreds of engineers.

Demonstrated success driving engineering transformation and organizational change across multiple teams and functions.

Strong executive presence, with proven ability to influence and align senior stakeholders across engineering, finance, IS&T, security, and privacy.

Excellent written and verbal communication skills; able to translate ambiguous, cross-organizational goals into clear technical direction for both technical and non-technical audiences.

Strong hiring, coaching, and performance management skills, with a track record of developing managers and senior ICs and retaining top talent.

Comfortable making sound decisions under pressure and operating effectively in ambiguity.

MS or PhD in Computer Science, Statistics, Engineering, or equivalent practical experience.

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