Senior Systems Engineer – Predictive Fleet Intelligence
On-siteHouston, Texas, United States
Job Summary
Define engineering specifications for fleet health monitoring, predictive detection rules, and alert architectures that enable Software Engineering and Data Science teams to develop scalable digital solutions. Translate root cause investigations and operational trends into reusable engineering standards, leading indicators, and response packages that reduce unplanned downtime and improve fleet reliability. Establish governance processes for monitoring strategies, dashboard requirements, and decision-support tools across industrial assets while partnering with Operations, Maintenance, and Technical Services. Conduct systematic reviews of alert effectiveness and detection logic to continuously expand predictive capabilities and minimize false positives. Requires travel to remote sites, variable hours including weekends and holidays, and ability to safely navigate work environments.
Required Qualifications
- Bachelor's degree in Mechanical Engineering, Electrical Engineering, Controls Engineering, Systems Engineering, Petroleum Engineering, or a related engineering discipline.
- Eight (8) or more years of experience in systems engineering, reliability engineering, industrial controls, automation, predictive maintenance, asset performance management, or complex industrial systems.
- Experience working with large-scale industrial equipment in asset-intensive industries such as drilling, mining, heavy equipment, manufacturing, marine, rail, power generation, or similar environments.
- Strong understanding of industrial control systems, instrumentation, condition monitoring technologies, and operational data platforms.
- Experience working with industrial historians, SCADA systems, PLC-based equipment, or time-series operational data.
- Working knowledge of Root Cause Analysis (RCA), Failure Modes and Effects Analysis (FMEA), reliability engineering, and predictive maintenance methodologies.
- Demonstrated experience developing engineering standards, technical specifications, system requirements, monitoring strategies, or equipment health frameworks.
- Experience collaborating with software engineering, digital product, or data science teams to deliver industrial monitoring or predictive analytics solutions.
- Ability to safely navigate work sites with occasional walking, climbing, standing, stepping, working at heights, etc., during normal operating conditions (day/night, outdoor hot/cold weather) and while utilizing designated personal protective equipment (PPE).
- Must be able to work in a time sensitive, high visibility role and regularly travel as needed to support business units and to visit work sites.
- It may also require extended travel to remote locations and/or overnight stay(s) during variable hours.
- Variable work hours include hours worked on the weekend, on holidays, and hours to travel within and outside of the assigned region.
Desired Qualifications
- Experience designing predictive maintenance or condition monitoring programs for complex industrial assets.
- Familiarity with machine learning, industrial analytics, digital twins, or asset performance management platforms.
- Knowledge of industrial networking, automation platforms, fleet management systems, and equipment health monitoring technologies.
- Experience defining engineering requirements for digital products or enterprise monitoring systems.
- Strong technical writing, analytical reasoning, and systems thinking skills.
- Excellent communication and stakeholder management abilities with experience influencing cross-functional engineering organizations.
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