Staff AI Platform Engineer – Model Infrastructure

United States Digital Space LLC

United States

Remote

USD 193,000 - 290,000

Full time

4 days ago
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Job summary

United States Digital Space LLC is seeking a Staff Software Engineer to lead the design and development of the Model Infrastructure powering AI requests across provider platforms. You will collaborate with AI Research, Product Engineering, and external providers to deliver reliable, scalable systems.

The role emphasizes ownership, fast iteration, and building a foundation for future AI workloads, with opportunities for growth and impact across the organization.

Qualifications

  • 4+ years of software engineering in large-scale distributed systems.
  • Experience operating production services with high availability.
  • Proficient in Go, Java, Python, Rust, or C++.
  • Strong knowledge of distributed systems, cloud infrastructure, networking, observability.
  • Proven ability to lead cross-team technical projects.
  • Excellent communication and collaboration skills.

Responsibilities

  • Build systems for high availability, low latency, and observability for AI inference.
  • Improve Unified Model Controller and Model Selector for traffic routing.
  • Develop provisioning, capacity management, failover, and traffic engineering across providers.
  • Integrate new model providers and maintain provider APIs/SDKs.
  • Improve observability with dashboards, alerts, token usage analytics, cost reporting.
  • Collaborate with Product Engineering to support model launches and monitoring.
  • Lead cross-functional technical initiatives and mentor engineers.

Skills

Distributed systems
Production services
Go
Java
Python
Rust
C++
Cloud infrastructure
Observability
Leadership
Communication

Tools

Kubernetes
Kafka
Spark
Flink
Airflow
Iceberg

Job description

United States Digital Space LLC is seeking a Staff Software Engineer to lead the design and development of the Model Infrastructure powering AI requests across provider platforms. You will collaborate with AI Research, Product Engineering, and external providers to deliver reliable, scalable systems.

The role emphasizes ownership, fast iteration, and building a foundation for future AI workloads, with opportunities for growth and impact across the organization.

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