Join the team redefining what a deeply personal and integrated assistant can be.

As part of the Siri organization, you will help shape one of the world's most widely used AI assistants, powered by our next-generation of Apple Intelligence, with capabilities like personal context understanding and on-screen awareness, built with privacy from the ground up. Your work will have direct, meaningful impact for users across iOS, iPadOS, macOS, watchOS, and visionOS.

This is a rare opportunity to build at the intersection of cutting-edge AI and human-centered design, shipping technology that is centered around users and their needs.

We are looking for a Distributed Systems Engineer to own the infrastructure powering our core Siri Agentic Evaluation Platform. Evaluation is no longer just a static test suite—it is a highly dynamic, massive-scale distributed problem. Our platform enables teams to run high-throughput agentic simulations, orchestrate multi-model judging pipelines, and generate real-time observability dashboards across billions of tokens and complex data types.

In this role, you will design the execution engine that coordinates these complex evaluation loops. You will build systems that remain deterministic, fault-tolerant, and cost-efficient, even when coordinating massive parallel requests across heterogeneous device types(iPhones, Mac, iPads etc).

+ 7+ years of experience as distributed systems engineer, platform engineer or equivalent

+ Systems & Backend Languages: Strong proficiency in languages optimized for concurrency and enterprise scale, such as Python (asyncio) or Java

+ API Design & Ecosystems: Deep expertise in designing robust, versioned production APIs using gRPC/Protobuf, GraphQL, or REST (FastAPI)

+ Relational & Analytical Databases: Strong experience modeling complex relational data and trace hierarchies using PostgreSQL, combined with high-throughput analytical query layers.

+ Orchestration & Messaging: Experience designing asynchronous, event-driven architectures using Kafka, AWS SQS/SNS, RabbitMQ, or Redis Streams.

+ Cloud Native Architecture: Advanced experience with Kubernetes (orchestration, custom operators, service meshes like Istio or Linkerd) and cloud providers (AWS, GCP, or Azure).

+ Experience building Agentic RAG platforms or developer-facing infrastructure tooling.

+ Infrastructure-as-Code (IaC): proficiency with Terraform to manage infrastructure declaratively.

+ CI/CD & DevEx: Experience building automated, containerized deployment pipelines (GitHub or ArgoCD) with an emphasis on keeping developer feedback loops fast and reliable.