Systems Validation & Integration Engineer - Modular Data Centers

We are seeking a highly driven and technically rigorous Senior Systems Validation & Integration Engineer to lead the end-to-end validation and integration of our modular data center platform.

This role is critical to ensuring that all subsystems-including power, cooling, controls, networking, compute infrastructure, software, monitoring, and mechanical systems-operate seamlessly as a fully integrated solution.

The position is based in Houston, TX and requires full-time onsite presence, as this individual will play a key role in building and operating our validation lab infrastructure. This role demands 100% commitment to the success of this project, from early integration through full system validation and deployment readiness.

What you will do

System Integration & Validation

• Lead end-to-end system validation of modular data center platforms across all subsystems

• Ensure seamless integration of electrical, mechanical, thermal, controls, networking, and compute components

• Define and execute validation strategies, test plans, and acceptance criteria

Lab Development & Testing Infrastructure

• Design, build, and scale the Houston-based validation lab environment

• Establish testing infrastructure, tools, and processes to support system-level validation

• Oversee lab operations, including test setup, instrumentation, and data collection

Cross-Functional Collaboration

• Work closely with engineering, product, manufacturing, software, and operations teams to ensure system readiness

• Coordinate integration activities across hardware, software, and infrastructure domains

• Act as the technical bridge between design, build, and deployment teams

Performance, Reliability & Troubleshooting

• Validate system performance under real-world and stress conditions

• Identify, isolate, and resolve integration issues across multiple subsystems

• Drive root cause analysis and corrective actions

Documentation & Reporting

• Maintain detailed validation reports, test results, and system performance data

• Provide clear updates to leadership on readiness, risks, and integration milestones

• Contribute to standards, best practices, and continuous improvement initiatives

• Bachelor’s or Master’s degree in Electrical Engineering, Mechanical Engineering, Systems Engineering, or a related field

• 7-10+ years of experience in systems integration, validation, or test engineering

• Hands-on experience with complex, multi-disciplinary systems (data centers, modular infrastructure, industrial systems, or similar)

• Strong understanding of:

• Power systems and electrical distribution

• Cooling systems (air and/or liquid)

• Networking and compute infrastructure

• Controls systems and monitoring platforms

• Experience building or managing lab / test environments is highly preferred

• Proven ability to diagnose and resolve complex integration issues

• Strong communication and cross-functional collaboration skills

Key Competencies

• Systems thinker with strong attention to detail

• Hands-on, problem-solving mindset

• Ability to operate in fast-paced, build-as-you-go environments

• High ownership and accountability

• Strong organizational and execution skills

• Attractive compensation package reflecting your expertise and experience.

• Medical Insurance Plan.

• 401k Employee volunteer contribution Plan.

• A great work environment characterized by friendliness, international diversity, flexibility, and a hybrid-friendly approach.

• You´ll be part of a fast-growing scale-up with a mission to make a positive impact, offering an exciting career evolution.

Our job titles may span more than one job level. The actual base pay is dependent on a number of factors, such as transferable skills, work experience, business needs, and market demands.

Submer designs and delivers end-to-end AI datacenter infrastructure built around industry-leading liquid cooling. We help organizations scale AI beyond the limits of traditional datacenters by enabling higher density, greater efficiency and lower environmental impact - accelerating time-to-AI from first deployment to full production.