Software Engineer - Fleet Automation Job Dallas area,Texas USA,Software Development

RESPONSIBILITIES

Design, build, and maintain fleet automation services and internal platforms for provisioning, configuration, and lifecycle management of large-scale GPU and CPU compute nodes.
Develop APIs and service integrations that enable Infrastructure and Operations teams to deploy, image, validate, and decommission hardware with minimal manual intervention.
Build and maintain backend services in Go, C#, and Type Script with a strong focus on reliability, testability, and long-term maintainability.
Design and evolve data models and persistent state for automation workflows, working across relational and No

SQL databases as appropriate.
Build and maintain CI/CD pipelines that gate configuration changes, run automated hardware validation tests, and promote changes safely across environments.
Instrument systems for observability — designing metrics, alerts, and dashboards in Prometheus and Grafana that provide real‑time fleet health visibility to on‑call teams.
Participate in on‑call rotations; own incident response, post‑mortems, and follow‑through on reliability improvements across the fleet.
Identify systemic gaps in fleet reliability and efficiency and champion engineering solutions that reduce operational toil at scale.

REQUIREMENTS

Bachelor’s Degree in Computer Science, Software Engineering, or equivalent practical experience.
5+ years of software engineering experience building production backend services or infrastructure automation tooling.
Proficiency in Go, C#, or Type Script.
Experience designing and working with relational and No

SQL databases to support stateful automation workflows and internal platform services.
Solid understanding of Linux systems — networking, storage, process management, and debugging on Ubuntu or RHEL variants.
Experience building and maintaining CI/CD pipelines and observability stacks (Prometheus, Grafana, Alert manager, ELK) in a production environment.
Familiarity with GPU compute infrastructure and NVIDIA tooling (DCGM, nvidia-smi, NVIDIA Container Toolkit) is a strong plus.
Exposure to event‑driven architectures or messaging platforms (e.g. Kafka) is a plus for teams building automation workflows across distributed services.
Strong communication skills and a collaborative mindset — comfortable navigating ambiguity, taking initiative, and working across Infrastructure, Operations, and Research teams.