{"id":4292730,"url":"https://alion.io/job/apple-sr-software-engineer-ai-data-platforms-aidp-2","title":"Sr. Software Engineer, AI & Data Platforms (AiDP)","company":{"id":12,"name":"Apple","domain":"apple.com","url":"https://alion.io/company/apple","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Apple Jobs","truth_index":{"grade":"A","score":94,"open_postings":607,"ghost_share":0.002,"stale_share":0.005,"repost_share":0.082,"time_to_fill_p50_days":149,"computed_at":"2026-11-14T05:58:10Z"}},"role":"Backend","role_family":"Backend","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Sunnyvale, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"C++","optional":false},{"name":"Java","optional":false},{"name":"Kotlin","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Cassandra","optional":true},{"name":"DynamoDB","optional":true},{"name":"MySQL","optional":true},{"name":"Oracle","optional":true},{"name":"PostgreSQL","optional":true},{"name":"SLI/SLO/SLA","optional":true},{"name":"SQL","optional":true}],"status":"live","first_seen_at":"2026-11-13T23:38:53Z","employer_posted_date":"2026-11-13","last_verified_at":"2026-11-14T12:03:10Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"AI & Data Platforms (AiDP) is IS&T's engine for AI-powered innovation. The team brings together data, application development, and machine learning - including generative AI - along with data services and customer success functions, to help IS&T build solutions more efficiently and streamline the adoption and embedding of generative AI across Apple.\nDescription\nWe’re looking for a hands-on Software Engineer to build and scale platform services that protect data privacy across a diverse database ecosystem, spanning on-premise and multi-cloud environments. You’ll design and ship the solutions that enforce privacy and security at scale. You’ll work closely with a collaborative team, and you’ll also own your work end to end. Your work will give teams a consistent way to discover, classify, and protect sensitive data wherever it lives, so privacy is built into the platform rather than added afterward. You’ll solve problems that cut across databases, cloud providers, and security requirements, and your solutions will directly shape how data is handled across the organization.\nMinimum Qualifications\n5+ years of software development experience\nExperience building highly available software services or platform infrastructure\nExperience designing, building, and maintaining API-driven microservices\nProficient in Python optionally Java/Kotlin/C/C++\nHands-on development experience with cloud platforms - AWS, AliCloud (or similar)\nBachelor's or Master's degree in Computer Science, CyberSecurity or related work experience\nPreferred Qualifications\nExperience applying GenAI and machine learning to privacy use cases, such as sensitive data discovery and classification, PII detection, and anomaly detection or user behavior analytics (UBA) to spot unusual access to personal data\nSolid understanding of service-level objectives (SLOs) for privacy and data protection, such as data subject request turnaround, retention and deletion compliance, and classification coverage\nAbility to measure, report, and enforce them through automation and visualizations\nSelf-starter with excellent interpersonal skills, able to work with cross-functional teams (engineering, security, legal, and compliance) and communicate privacy requirements clearly to stakeholders at all levels of management\nHands-on experience with diverse SQL and NoSQL databases (e.g., PostgreSQL, MySQL, Oracle, MongoDB, Cassandra, DynamoDB) and an understanding of how to apply privacy controls such as encryption, masking, access control, and auditing across different data models and 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