Job Details

Role Number: 200633452-0157

Summary

We're seeking a Database Engineer to architect and optimize our large-scale RAG (Retrieval-Augmented Generation) platform that serves our users across all of the Hardware Tech group. This role combines deep database expertise with modern AI/ML infrastructure, enabling design teams to seamlessly onboard and query enterprise-scale datasets. You'll be responsible for database architecture and optimization while also contributing to full-stack GenAI application development.

Description

As a Database Engineer on our team, you will architect and optimize our SQL and vector database infrastructure supporting enterprise-scale design data. You'll lead technical decisions on database architecture, scaling patterns, and technology selection for our RAG platform while designing comprehensive strategies to ensure optimal performance. Working closely with the development team, you'll build and refine data ingestion pipelines that enable design teams across all disciplines to seamlessly onboard their data. You'll collaborate with DevOps/SRE teams to ensure quality of service, proper resource allocation, and system scalability while improving RAG retrieval performance through hybrid search strategies, index tuning, and embedding optimization. In addition to your primary database focus, you'll contribute to full-stack development using Python and JavaScript, monitor database health and performance metrics for our multi-tenant system, and develop and maintain database operations procedures, monitoring, and disaster recovery strategies while driving continuous improvement of retrieval quality, search latency, and overall system reliability. You'll also provide mentorship to other engineers on database best practices and scalable design patterns.

Minimum Qualifications

• Proficiency in Python or Javascript.

• Production experience deploying and managing vector databases (Milvus, Qdrant, or Weaviate) at scale

• Experience with PostgreSQL or MySQL in production environments

• Understanding of RAG pipelines, including embedding strategies, chunking, and retrieval optimization

• Minimum requirement of BS + 10 years of relevant industry experience

Preferred Qualifications

• Understanding of Vector database indexing strategies and tradeoffs

• Strong SQL proficiency with deep understanding of query planning, indexing strategies, and optimization techniques

• Postgres advanced features (extensions, replication, sharding)

• Experience managing large-scale databases serving high-concurrency workloads

• Experience with embedding models and LLM integration patterns

• Demonstrated experience building or optimizing RAG systems in production environments

• Collaborative mindset with ability to mentor engineers and work closely with DevOps/SRE teams

• Monitoring and observability tools (Prometheus, Grafana)

• Kubernetes experience, particularly with stateful applications and database deployments

• Proven ability to make architectural decisions for scalable database systems

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf) .