Systems Engineer - Evaluation Engineering

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.

Description

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).

Responsibilities:

Distributed Execution Engine: Architect and scale the core asynchronous engine responsible for orchestrating thousands of parallel agent simulations, validation tests, and LLM-as-a-judge pipelines.

Internal Developer Platform (IDP): Design and build self-service infrastructure, CLI tools, and internal APIs that allow ML and product teams to easily integrate evaluation pipelines into their CI/CD workflows.

Backend API & Service Architecture: Design, build, and maintain highly performant, type-safe APIs (gRPC/REST) capable of serving complex evaluation pipelinee, trace data, and real-time generation metrics.

Stream Processing & Lineage: Build robust data pipelines to ingest and transform high-volume execution traces. Ensure immutable data lineage so that every evaluation metric can be perfectly traced back to its raw generation for granular error attribution.

Infrastructure-as-Code & GitOps: Own the deployment topologies of the evaluation platform across multi-tenant clusters using declarative infrastructure and continuous delivery practices.

Reliability, Observability & Guardrails: Implement deep observability (distributed tracing, structured metrics, and alerting) across the platform. Design smart scheduling layers, token buckets, and circuit breakers to prevent downstream API rate-limiting or cascading cluster failures.

Preferred Qualifications

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.

Minimum Qualifications

MS in computer science or equivalent

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)

Pay & Benefits

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $184,700 and $324,800, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.