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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Engineering Manager - Foundations, Finance Data & Technology - **Company:** Apple Inc. - **Location:** Cupertino, CA, United States - **Experience:** Expert - **Salary:** $237,600.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Application Frameworks, Cloud Computing, Cloud Engineering, Programming Tools, Distributed Systems, Graph Database, IT Management, Open Source Technology, Azure Machine Learning, Software Engineering, Evaluation Pipelines, Retrieval-Augmented Generation, Generative AI, Information Technology, Data Management, Machine Learning Operations - **Published:** October 15, 2026 - **Apply:** https://www.jobmonkeyjobs.com/career/28110073/Engineering-Manager-Foundations-Finance-Data-Technology-California-Cupertino-7413 ## About the Role 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. ## Description In this role, you will own the strategy, architecture, and execution of finance 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. Responsibilities Own strategy, architecture, and execution for the Foundations platform, including cloud infrastructure, data platforms, application frameworks, developer tooling, and AI/ML services. Lead the build-out of production-grade agentic AI and GenAI capabilities as reusable enterprise assets, not isolated pilots, including model lifecycle management, evaluation pipelines, observability, and responsible AI governance. Serve as the primary engineering point of contact with IS&T and other engineering organizations, negotiating shared standards, integration points, and platform dependencies. Partner with business-facing delivery pods, finance leadership, security, privacy, and legal to align the platform roadmap with enterprise priorities. Manage and develop a team of engineering managers, architects, and senior technical leads; build clear career paths and succession plans. Establish engineering standards, architectural principles, and reference patterns that raise the bar on quality, reliability, and security across all consuming teams. Define and report platform health metrics, including adoption, developer productivity, deployment velocity, and reliability, to executive stakeholders. Drive platform modernization and cost efficiency while scaling to support rapid growth in data volume, AI use cases, and consuming teams. Communicate platform strategy and trade-offs clearly to both technical teams and non-technical business partners, building trust and alignment across the organization. Balance near-term delivery pressure with long-term investment in platform health, governance, and scalability.