Senior Software Engineer

Responsibilities

• Design, build, and operate highly available data and AI infrastructure on Kubernetes and public cloud platforms.
• Develop platforms for streaming, batch processing, and real-time workloads using Kafka, Spark, and Flink.
• Build AI gateways, model-routing layers, traffic management, rate limiting, authentication, observability, and usage controls.
• Develop self-service platform capabilities that enable data, AI, and application teams to deploy and operate workloads independently.
• Partner across engineering disciplines to translate data and AI requirements into durable platform capabilities.
• Improve infrastructure scalability, reliability, operational efficiency, visibility, capacity, and cost.

Requirements

• 5+ years of experience in DevOps, SRE, or platform engineering owning production systems end to end.
• Strong experience designing, operating, and troubleshooting production Kubernetes environments.
• Experience with distributed data infrastructure such as Kafka, Spark, or Flink, or with AI infrastructure such as AI gateways or model-routing platforms.
• Hands-on experience with at least one major public cloud platform, including AWS, Google Cloud, or Microsoft Azure.
• Strong knowledge of cloud and container networking, including DNS, load balancing, ingress, service discovery, TLS, routing, and network security.
• Proficiency in one or more of Go, Python, or Java and experience writing maintainable production software.
• Understanding of distributed-systems concepts including availability, consistency, fault tolerance, backpressure, and horizontal scalability.
• Experience operating critical infrastructure with infrastructure-as-code, automated delivery, and modern observability practices.
• Strong debugging, communication, collaboration, and ownership skills.
• Preferred experience includes internal developer platforms, paved-road workflows, SGLang, vLLM, NVIDIA Triton Inference Server, GPU scheduling, batching, model parallelism, memory management, autoscaling, inference optimization, cost efficiency, or relevant open-source contributions.

Benefits

• Hybrid work arrangement based in Seattle, Washington.