Systems Engineer - Evaluation Engineering
Job details
- Level
- Senior
- Experience
- 7+ years
- Education
- Master's degree
- Posted
- Oct 22, 2026
- Last confirmed open
- Oct 25, 2026
About this role
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.
We are looking for a Distributed Systems Engineer to own the infrastructure powering our core 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).
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).
Cloud Native Architecture
Advanced experience with Kubernetes (orchestration, custom operators, service meshes like Istio or Linkerd) and cloud providers (AWS, GCP, or Azure).
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. 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.