Software Engineer -Automation

Vertiv•Austin, TX

18h•Onsite

About The Position

We are seeking a Systems Software Engineer – Validation Automation & AI to join our dynamic team. This role is intended for a software engineer who can operate across Linux-based control system platforms, embedded device communication, automated test frameworks, and AI-enabled engineering systems. The primary focus is on developing scalable validation strategies, test automation infrastructure, and system-level verification for thermal and datacenter infrastructure control software platforms. In addition to traditional validation and automation responsibilities, this role will explore and implement practical agentic AI solutions to accelerate test development, automate test generation and maintenance, improve diagnostics and root-cause analysis, expand engineering knowledge access, and enhance overall engineering productivity. The ideal candidate will help define how AI agents can be leveraged throughout the software validation lifecycle—from requirements analysis and test-case creation to regression testing, failure investigation, and continuous quality improvement. You will contribute to software platforms used in critical thermal and infrastructure environments, where reliability, observability, maintainability, and technical rigor matter. Candidates should be comfortable working at the intersection of systems software, validation engineering, automation tooling, and emerging AI technologies.

Requirements

Degree in a STEM field such as Computer Science, Electronic Engineering, Automation, Physics, or equivalent practical experience
Strong software engineering skills in Python
Good working knowledge of C/C++ in systems, embedded, or performance-sensitive environments
Solid understanding of Linux systems, command-line tooling, process management, networking basics, and Bash scripting
Experience building modular software components, services, or tooling with attention to maintainability and technical quality
Experience with one or more communication technologies such as Modbus, MQTT, CANbus/CANopen, serial protocols, TCP/IP-based device integration, or similar
Experience with Docker, containerized development environments, or service-based deployment workflows
Familiarity with CI/CD practices and version control workflows
Ability to work across disciplines and deal with real-world engineering constraints, incomplete information, and integration complexity
Fluent English, written and spoken

Nice To Haves

Experience designing software that combines deterministic logic with AI-driven components in a robust and observable way
Background in embedded Linux systems
Familiarity with diagnostics, observability, system logging, tracing, or performance analysis tools
Experience creating developer tooling, internal platforms, or technical productivity systems
Familiarity with REST APIs, WebSocket-based services, or integration middleware
Experience contributing to interface documentation, technical platform specifications, or reusable software standards

Responsibilities

Design and implement software components and services in Python and C/C++ for Linux-based thermal and infrastructure platforms
Develop modular software for embedded control systems, including data acquisition, diagnostics, orchestration, and device interaction
Validate communication and integration layers using protocols such as Modbus RTU/TCP, Redfish, SNMP, MQTT, and similar field protocols
Create internal tooling and engineering utilities for configuration, deployment, troubleshooting, validation, and system analysis
Debug, analyze, and optimize system behavior across software, communications, devices, and test infrastructure to identify and resolve quality issues
Translate requirements, interface specifications, communication protocols, and system documentation into automated validation workflows, reusable test assets, and machine-executable test procedures
Establish validation strategies, test architectures, traceability practices, and quality metrics that support reliable and maintainable software releases
Write and maintain automation, integration, deployment, and CI/CD tooling to support continuous validation and regression testing
Evaluate and deploy AI agents capable of generating test cases, creating validation artifacts, analyzing failures, identifying coverage gaps, and assisting with root-cause analysis
Contribute to software architecture decisions, including modularity, interface design, service boundaries, and long-term maintainability
Produce and maintain high-quality technical documentation, including module descriptions, interface contracts, workflow definitions, and integration guidance
Collaborate closely with product stakeholders to identify high-value software and AI automation use cases