Senior Backend Developer

Senior Software Engineer, HPC Scheduling

Type:
Direct Hire

Relocation:
Available for non-local candidates

Compensation:
Base salary: $170,000 - $250,000 + performance bonus

GTN is seeking a Senior Software Engineer, HPC Scheduling to help design, build, and maintain large-scale scheduling software that supports demanding HPC, AI, research, and production workloads.

This role sits on a highly technical engineering team responsible for developing distributed systems, backend services, APIs, tooling, and automation that keep a high-scale compute platform reliable, performant, and maintainable.

Much of the work centers around Armada, an open-source project built and maintained by the team, along with internal scheduling, orchestration, and platform services. The current codebase is primarily written in Go, but the team is open to strong backend engineers from any language background as long as they have experience building production software at scale and can ramp into Go.

This is a hands-on engineering role focused on writing clean, well-tested code, reviewing designs, solving complex distributed systems problems, and owning production-quality software.

The ideal candidate is a strong backend engineer with excellent coding fundamentals, experience building scalable services or distributed systems, and a practical understanding of how software runs in cloud, Linux, Kubernetes, and production infrastructure environments.

• Design, write, test, and review high-quality production code, primarily in Go
• Build and maintain scalable backend services, APIs, and distributed systems supporting high-demand workloads
• Contribute to Armada and related internal scheduling, orchestration, and platform services
• Develop tooling and automation that improves platform reliability, developer productivity, and operational efficiency
• Apply strong software architecture principles to ensure systems are maintainable, correct, and scalable
• Collaborate with senior engineers on technical design, code reviews, system improvements, and long-term platform direction
• Build services that operate reliably across large-scale HPC and AI infrastructure environments
• Design backend systems that support high-volume workloads, complex scheduling logic, and distributed execution patterns
• Work with Kubernetes-based orchestration, containerized services, and modern deployment workflows
• Develop and debug software in Linux environments using command-line and system-level tooling
• Apply networking and systems fundamentals to troubleshoot, optimize, and improve platform performance
• Independently diagnose and resolve complex issues across software and infrastructure layers

• Manage and optimize data interactions across relational and non-relational data stores, with emphasis on PostgreSQL
• Contribute to CI/CD pipelines, automated testing, observability, and engineering best practices
• Use monitoring, logging, and runtime tools such as Prometheus, Grafana, or similar platforms
• Think critically about correctness, edge cases, performance, scalability, and failure modes
• Support production-quality engineering practices across testing, reliability, documentation, and maintainability
• Stay current with emerging technologies and apply new approaches where they improve platform outcomes

• Strong backend software engineering fundamentals, including data structures, algorithms, system design, and maintainable code practices
• Professional experience building backend services, APIs, distributed systems, platform services, or infrastructure software in production environments
• Proficiency in Go, Java, C++, C#, Rust, Scala, Kotlin, Python, or another production backend language
• Ability and willingness to ramp into Go-based codebases
• Experience building software at scale, ideally in environments involving high throughput, distributed workloads, reliability requirements, or complex production systems
• Familiarity with cloud environments such as AWS, GCP, or Azure
• Experience with Linux-based development and debugging
• Familiarity with Kubernetes, containers, or modern deployment pipelines
• Ex…