Software Engineer - Regulatory AI & Connected Data

Senior Software Engineer - Regulatory AI & Connected DataAt Apple, the Product Analysis and Compliance Engineering (PACE) organization ensures that every product we ship meets the highest standards of regulatory compliance, product safety, and analytical rigor. We operate at the intersection of engineering, compliance, and data, delivering the insights, testing, and certification workflows that Apple's product programs depend on. Our teams navigate complex regulatory landscapes across dozens of global markets, managing a volume and velocity of compliance work that grows with every product Apple ships. PACE is building intelligent systems at the intersection of AI, connected data, and compliance, making the organization dramatically more efficient. Our work connects disparate data sources, applies AI to extract insight and automate decision-making, and puts powerful tools directly in the hands of compliance engineers and analysts. We are seeking a Software Engineer who believes the best way to build great software is to ship early, measure relentlessly, and iterate based on real feedback and real data.As a Senior Software Engineer on this team, you will design, build, and ship software systems that apply AI to improve the efficiency of the PACE team. You will work in small iterations, delivering working software early and often, and use data to guide what to build next. You believe that quality is built in - not bolted on - and that fast delivery and high standards reinforce each other. You will help establish the engineering culture of a new team: lean practices, continuous delivery, production observability, and a relentless focus on outcomes over output. You are deeply curious - about emerging AI capabilities, how users actually work, and how to make tools to enable success - and you channel that curiosity into building things that matter. You will collaborate closely with PACE domain experts to deeply understand their problems, and with data and AI practitioners to build systems that genuinely work at scale.Design, build, and ship AI-powered software systems that improve team efficiency, delivering incrementally and iterating based on user feedbackApply secure engineering practices throughout: secrets management, data classification, access control, and audit logging appropriate for compliance-sensitive dataBuild and maintain robust data pipelines that connect corporate data sources, ensuring data quality, lineage, and accessibilityEffectively use & improve leading agentic harnesses to build software with your principles, through the development of skills, agents and MCPsIntegrate AI and large language models into production systems with appropriate evaluation, guardrails, and monitoring - treating models as components, not magic.Ensure that there is an audit trail for traceability/lineage for AI/LLM based decisionsEstablish and maintain continuous delivery pipelines, optimizing for the DORA metrics: deployment frequency, lead time, change failure rate, and mean time to recoveryBuild observability into every system from day one - instrumentation, structured logging, alerting, and dashboards that give the team confidence to ship fastWrite clean, testable, well-factored code; practice continuous integration, continuous refactoring, and small batch delivery as daily habitsActively explore the PACE team's domain, emerging tools, and adjacent problem spaces - bring new ideas and challenge assumptionsWork directly with PACE team's domain experts to understand problems deeply before building solutionsCollaborate across teams and organizations to integrate data sources and align on technical directionContribute to the engineering culture of a new team - shaping practices, running retrospectives, and helping the team continuously improveRepresent your work through demos, design discussions, and clear written communicationMinimum QualificationsBachelor's Degree in Computer Science, Computer Engineering, related field, or equivalent work experience7+ years experience building and shipping production software systemsStrong track record of delivering AI-powered systems at scale, including model integration, evaluation, and production monitoringDeep practical experience with modern software engineering practices: continuous integration, continuous delivery, trunk-based development, and incremental deliveryProficient in Python and at least one other high-level programming languageExperience building data pipelines and working with connected data across multiple sourcesExperience with cloud infrastructure and container technologies including Kubernetes and DockerDemonstrated ability to build observability into production systems - metrics, tracing, logging, and alertingA curious mindset - you dig into unfamiliar domains, ask why things work the way they do, and seek out knowledge beyond your immediate responsibilitiesExcellent written and verbal communication skills with both technical and non-technical audiencesPreferred QualificationsMaster's degree in Computer Science, Computer Engineering, related field, or equivalent work experienceExperience working in or building software for regulated industries (compliance, legal, safety, or similar domain)Familiarity with the principles in Accelerate and practical experience improving DORA metrics in a team settingExperience with test-driven development, continuous refactoring, small batch delivery, and collective code ownershipExperience securing AI/LLM systems that process sensitive or regulated data, including prompt injection defense, data handling policies, and audit trail requirementsExperience with LLM application patterns: retrieval-augmented generation, prompt engineering, evaluation frameworks, and human-in-the-loop workflowsExperience with MLOps practices including model versioning, experiment tracking, and performance monitoring in productionTrack record of building systems that connect and make sense of heterogeneous data sources at enterprise scaleExperience helping establish engineering culture on a new or transforming teamPay & BenefitsAt Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $184,700 and $324,800, and your base pay will depend on your skills, qualifications, experience, and location. Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation.