Java Developer (EX Apple)

Mountain View, CA

Mode of Interview: Phone + Video

Job Description:

NEED MINIMUM 3 YEARS EXPERIENCE WORKING IN APPLE

• Drive significant technical initiatives end-to-end, from functional requirements through technical specification, test planning, and production rollout
• Act as the technical subject matter expert on agentic execution systems — solve through hard, unprecedented programming and design problems
• Prototype and validate proofs of concept quickly; use AI-assisted development tools fluently as part of your own workflow, not just as a subject you build for
• Generate technical documentation that communicates architectural and design tradeoffs clearly to both engineering teams and business stakeholders
• Operate in Agile/Scrum cadences while retaining the independent judgment to make calls the backlog hasn't anticipated yet
• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience; 3+ years building cloud-based platforms or services
• 8+ years developing systems/software for large-scale environments (Java, Springboot), with demonstrated ability to design for scale quickly rather than needing a decade to build the instinct
• Hands-on experience building with AI: you've shipped something using LLM APIs, agentic frameworks, or AI-assisted coding tools as a core part of the system, not as an add-on. Comfortable reasoning about prompt-driven execution, model behavior under load, and the failure modes that come with non-deterministic systems
• Fluent daily user of AI-assisted development tools (Claude Code, Cursor, Copilot, or similar) — this role expects you to build faster because of AI, and to bring that instinct to designing infrastructure where AI agents are the primary actor
• Practical experience with microservices and messaging technologies (Micro services, REST, GraphQL, Kubernetes, Kafka, ActiveMQ) and database design across SQL (MySQL) and NoSQL (DynamoDB, Cassandra)
• Some exposure to the cost/performance mechanics of running LLMs in production — rate limits, token economics, caching strategies, orchestration patterns — is a strong plus even without years of tenure in the space, since almost nobody has years of tenure here yet
• Strong CS fundamentals: data structures, algorithms, and system design intuition that holds up with no reference architecture to copy
• Working knowledge of TDD and SDLC practices, with the judgment to know when rigor matters and when speed does
• A builder's bias toward shipping working prototypes over long design docs, balanced with the discipline to document architecture decisions clearly once validated
• Self-starter who makes decisions independently in ambiguous, fast-moving conditions, and communicates clearly across technical and non-technical audiences
• Comfortable working across global teams and time zones in a fast-paced, high-adaptability environment