Senior Software Engineer, High-Performance Computing (HPC) Scheduling & Distributed Systems

Senior Software Engineer, HPC Scheduling

Location: Dallas, TX | Hybrid

Type: Direct Hire

Relocation: Available for non-local candidates

Compensation

Base salary: $170,000 – $250,000 + performance bonus

Benefits: 100% company-paid benefits

Overview

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 scheduling 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 services and platform tooling written primarily in 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 software engineer with excellent coding fundamentals, experience building backend or distributed systems, and a practical understanding of how software runs in cloud, Linux, Kubernetes, and production infrastructure environments.

Key Responsibilities

Software Engineering & Platform Development

• 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

Distributed Systems & Infrastructure

• Build services that operate reliably across large-scale HPC and AI infrastructure environments

• 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 fundamentals to troubleshoot, optimize, and improve platform connectivity and performance

• Independently diagnose and resolve complex issues across software and infrastructure layers

Data, Reliability & Operations

• 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, and failure modes

• Stay current with emerging technologies and apply new approaches where they improve platform outcomes

Required Experience

• Strong software engineering fundamentals, including data structures, algorithms, system design, and maintainable code practices

• Proficiency in Go or another statically typed language, with the ability to quickly ramp into Go-based codebases

• Experience building backend services, APIs, distributed systems, or infrastructure software in production environments

• 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

• Experience with PostgreSQL or similar relational databases

• Understanding of observability practices, including monitoring, logging, metrics, and alerting

• Strong testing mindset with focus on correctness, reliability, and failure scenarios

• Ability to work independently, review code thoughtfully, and contribute in a collaborative engineering team

Preferred Experience

• Experience with HPC, AI infrastructure, batch scheduling, workload orchestration, or large-scale compute platforms

• Hands-on experience with Kubernetes scheduling, multi-cluster systems, or distributed job orchestration

• Contributions to open-source projects or experience working in open-source engineering environments

• Experience with non-relational databases, message queues, event-driven systems, or high-throughput platforms

• Familiarity with performance optimization, reliability engineering, or production platform operations

Ideal Profile

The ideal candidate is a hands-on software engineer who enjoys building infrastructure software that operates at scale. They write clean, tested code, understand distributed systems tradeoffs, and are comfortable working close to production infrastructure. They do not need to come directly from an HPC background, but they should have strong backend engineering fundamentals and an interest in solving complex scheduling, orchestration, and platform reliability challenges.

Why This Role

• Work on high-scale HPC and AI infrastructure supporting demanding production workloads

• Contribute to Armada, an open-source scheduling platform

• Join a senior, collaborative engineering team with real ownership over technical direction

• Build software that directly impacts platform reliability, performance, and scalability

• Competitive compensation, performance bonus, relocation support, and 100% company-paid benefits