Software Engineer - Fleet Automation

Career Techniques; Dallas (TX); Hybrid; USD 120,000 - 160,000; Full time

Job summary

Career Techniques in Dallas, TX seeks an experienced backend engineer to design, build, and maintain fleet automation services and internal platforms for provisioning, configuration, and lifecycle management of large-scale GPU and CPU compute nodes. You will develop APIs and service integrations, build and maintain backend services, and instrument systems with Prometheus and Grafana to ensure reliability.

Proficiency in Go, C#, or TypeScript is required with 5+ years of production backend

Qualifications

• Bachelor’s degree or equivalent practical experience in CS, software engineering, or related field.
• 5+ years of software engineering experience building production backend services or infrastructure automation tooling.
• Proficiency in Go, C#, or TypeScript.
• Experience with relational and NoSQL databases to support stateful automation workflows.
• Solid understanding of Linux systems and debugging on Ubuntu or RHEL.
• Experience building and maintaining CI/CD pipelines and observability stacks (Prometheus, Grafana, ELK).
• Exposure to GPU compute infrastructure and NVIDIA tooling is a strong plus.

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 to enable deployment, imaging, validation, and decommissioning with minimal manual intervention.
• Build and maintain backend services in Go, C#, and TypeScript focusing on reliability and long-term maintainability.
• Design data models for automation workflows across relational and NoSQL databases.
• Build CI/CD pipelines that gate changes and run automated hardware validation tests.
• Instrument systems for observability with metrics, alerts, and dashboards (Prometheus, Grafana).
• Participate in on-call rotations; own incident response and reliability improvements across the fleet.
• Identify gaps and champion engineering solutions to reduce operational toil at scale.

Skills

Go

C#

TypeScript

Linux

CI/CD

Observability

Communication

Education

Bachelor’s Degree in Computer Science or related field

Tools

Prometheus

Grafana

ELK

Kafka

DCGM

nvidia-smi

NVIDIA Container Toolkit

Job description

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 TypeScript 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 NoSQL 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 TypeScript.
• Experience designing and working with relational and NoSQL 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, Alertmanager, 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.