Senior Sr Engineering Manager - Services Special Projects - Jobs - Careers at Apple
- Hire, lead, mentor, and grow a team of senior distributed systems engineers; scale the team and its processes as the project expands.
- Own the architecture, design, and delivery of highly distributed systems and microservices built for scalability, high availability, fault tolerance, and low latency.
- Lead the operationalization of ML workloads in production, including model serving, inference performance, capacity planning, rollout strategies, and monitoring of model behavior in the transaction path.
- Partner with SRE to set and uphold operational excellence: SLOs/SLIs, comprehensive monitoring and alerting, on-call health, incident response, and blameless postmortems.
- Drive data modeling and storage strategy across transactional databases, NoSQL stores, caching layers, and event streaming systems, ensuring correctness, consistency, and durability.
- Work with Data Engineering to design reliable data pipelines and feedback loops between online services and offline analytics/ML training systems.
- Collaborate with client and iOS teams to define performant, well-versioned service APIs and contracts that deliver great customer experiences.
- Establish engineering best practices across design reviews, code quality, testing, CI/CD, security, and privacy.
- Communicate clearly with senior leadership and cross-functional stakeholders on strategy, priorities, trade-offs, risks, and progress.
- Foster an inclusive, collaborative team culture built on ownership, learning, and technical excellence.
- Bachelor's or Master's degree in Computer Science or a related field, or equivalent experience.
- 15+ years of professional software development experience, including building and operating large-scale distributed systems in production.
- 8+ years of people management experience leading teams of senior backend or distributed systems engineers, including hiring and growing teams.
- Proven track record of taking a new service from concept to production at scale and owning its long-term operation.
- Deep expertise in architecting multi-tiered distributed systems and microservices: API design, authentication and authorization, concurrency, scaling for high availability, fault tolerance, and reliability.
- Strong background in the Java/JVM ecosystem (e.g., Spring Boot, async/reactive frameworks such as Netty or Project Reactor) and RPC frameworks such as gRPC.
- Deep understanding of transactional consistency models, ACID semantics, and the trade-offs between relational and NoSQL database technologies.
- Experience with event streaming and queueing systems (e.g., Kafka), stream processing, and caching technologies (e.g., Redis) in production services.
- Experience running services on AWS or GCP with cloud-native tooling (Docker, Kubernetes) and mature CI/CD pipelines.
- Strong operational mindset: experience defining SLOs, building observability (metrics, logging, tracing, alerting), and leading incident response for customer-facing services.
- Experience deploying and operating ML models or ML-powered services in production environments.
- Excellent communication skills and the ability to influence and align senior cross-functional partners.
- Experience building search, ranking, recommendation, or personalization systems.
- Hands-on experience serving and optimizing LLMs or ML models in the request path, including GPU-backed inference at scale.
- Familiarity with MLOps practices: model versioning, feature stores, A/B testing and experimentation, and model monitoring.
- Experience partnering with client and mobile teams on API design, data contracts, and end-to-end performance.
- Experience with data lake and analytics technologies (e.g., Iceberg, Spark) and schema tooling (Protobuf, Avro, Schema Registry).
- Background in security and privacy: TLS, X.509 certificates, OAuth2/OIDC, threat modeling, and privacy-preserving system design.
- Experience growing a team from early stage to a multi-team organization, including developing senior engineers and future leaders.
- Self-motivated and comfortable with ambiguity, with experience in fast-paced, agile environments.
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Required Skills
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🇬🇧 English