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Senior Backend Software Engineer

Union AI

full-remoteseniorpermanentbackend Full remote Today via WTTJ

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Tags

GoDistributed SystemsAWSGCPAzureKubernetesPerformance Optimizationp99 LatencyInfrastructure as CodeMachine Learning Infrastructure

About the role

Role Overview

Join Union AI as a Senior Backend Software Engineer to build the infrastructure powering AI workloads at scale. You’ll design and implement core services in Go, optimize system performance, and collaborate closely with ML engineers and platform teams.

Key Missions

  • Design & implement core backend services in Go across multiple cloud environments.
  • Optimize system performance across compute, memory, and network; identify bottlenecks and deliver measurable improvements.
  • Partner with ML and platform teams to understand workload characteristics and design systems that meet reliability and latency needs.

Profile / Requirements

  • 5+ years building production backend systems with strong Go proficiency.
  • Significant experience with multiple major cloud providersAWS, GCP, and Azure—including compute, networking, and IAM.
  • Experience designing and operating large-scale distributed systems with high availability, fault tolerance, and horizontal scaling.
  • Familiarity with Kubernetes and cloud-native/container orchestration patterns.
  • Deep performance optimization skills (e.g., profiling code, interpreting flame graphs, reasoning about p99 latency).
  • Strong communication and collaborative problem-solving.

Nice-to-haves

  • Contributions to open-source.
  • Experience building infrastructure for ML/AI workloads (training, inference, data pipelines).
  • Infrastructure-as-Code experience (e.g., Terraform or Pulumi).
  • Experience with Python and/or Rust for SDK/tooling.
  • Background in systems programming, networking, or storage.

Location / Remote Policy

  • Role is full remote, but if you’re in the Seattle/Bellevue area, expect in-office presence on a hybrid schedule.

About Union AI

Union AI builds cloud infrastructure for running AI workloads at scale. The company focuses on backend services, distributed systems, and platform engineering to deliver reliable, low-latency performance for ML/AI teams.

Scraped 5/13/2026

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