{"id":1818634,"url":"https://alion.io/job/patenergy-senior-systems-engineer-predictive-fleet-intelligence","title":"Senior Systems Engineer – Predictive Fleet Intelligence","company":{"id":2504637,"name":"Patterson-UTI","domain":"patenergy.com","url":"https://alion.io/company/patenergy","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"B","score":75,"open_postings":38,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-13T05:45:00Z"}},"role":"DevOps","role_family":"DevOps","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Houston, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":112000,"max_usd":220000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1413},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Digital Twin","optional":false},{"name":"Machine Learning","optional":false},{"name":"Time Series Forecasting","optional":false}],"status":"live","first_seen_at":"2026-07-23T22:20:08Z","employer_posted_date":"2026-07-23","last_verified_at":"2026-10-13T17:34:49Z","board_verified":true,"closed_at":null,"days_open":81,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":81},"description":"The Senior Systems Engineer - Predictive Fleet Intelligence is the engineering authority responsible for defining how fleet health is monitored, how developing equipment failures are detected, and how engineering knowledge is transformed into scalable digital solutions.\nServing as the domain expert for predictive fleet intelligence, this role establishes the engineering requirements, monitoring strategies, detection logic, alerting philosophy, and technical specifications that enable Software Engineering and Data Science teams to develop predictive monitoring applications, fleet intelligence products, and operational decision-support tools.\nRather than developing software or analytics models directly, this engineer defines what should be monitored, why it matters, how abnormal behavior should be identified, and what actions should result. Success is measured by reducing unplanned downtime, improving fleet reliability, increasing early fault detection, and continuously expanding the organization’s predictive engineering capabilities.\nWorking across Engineering, Reliability, Operations, Controls, Technical Services, Digital Solutions, and Data Science, this role transforms operational experience, root cause investigations, and equipment expertise into reusable engineering standards that improve the performance of an entire fleet of industrial assets.\nPrimary Deliverables\nThis role is responsible for developing and continuously improving the engineering products that enable predictive fleet intelligence, including:\nFleet Health Monitoring Specifications defining monitoring objectives, required data sources, operating thresholds, engineering logic, and alert behavior.\n\nPredictive Detection Rule Specifications that enable Software Engineering and Data Science teams to develop automated monitoring applications and predictive analytics.\n\nFailure Pattern & Leading Indicator Rules Library documenting confirmed failure signatures, detection criteria, engineering rationale, probable causes, and recommended operational responses.\n\nPredictive Alert Specifications defining alert context, response guidance, escalation logic, notification strategies, and acceptance criteria.\n\nFleet Health Dashboard & Operational Intelligence Specifications defining the engineering requirements for dashboards, reports, and digital decision-support products.\n\nStandardized Alert Response Packages enabling field operations and technical support teams to investigate and resolve predictive alerts without requiring engineering involvement.\n\nAlert Effectiveness Reports & Continuous Improvement Recommendations measuring monitoring performance, operational outcomes, false-positive trends, and opportunities to improve predictive monitoring capabilities.\n\nKey Responsibilities\nFleet Health Monitoring Strategy & System Design\nDefine the engineering strategy for monitoring the health and performance of complex industrial assets, including control systems, power systems, mechanical equipment, supporting infrastructure, communications networks, and deployed software configurations.\n\nAuthor detailed monitoring requirements that define what equipment should be monitored, what operating conditions represent normal performance, and what deviations indicate degradation or impending failure.\n\nEstablish system health logic, engineering thresholds, operating limits, and classification criteria that distinguish healthy operation from abnormal conditions.\n\nDefine data acquisition requirements by identifying the signals, parameters, instrumentation, and operational data necessary to support meaningful equipment health assessment.\n\nDevelop engineering specifications for predictive monitoring capabilities, documenting leading indicators, failure signatures, and detection logic that enable early identification of developing equipment failures.\n\nDevelop equipment-specific monitoring standards and predictive detection strategies for major asset classes across the fleet, defining how healthy operation, degradation, and impending failure manifest within operational data.\n\nDefine leading indicators and engineering detection criteria that enable developing equipment failures to be identified sufficiently in advance to support proactive operational intervention.\n\nDefine monitoring strategies for software version compliance and control system configuration management to ensure fleet-wide operational consistency.\n\nContinuously improve alarm rationalization and monitoring strategies to ensure operators receive timely, actionable information while minimizing nuisance notifications.\n\nAuthor engineering specifications that Software Engineering and Data Science teams use to develop fleet-wide monitoring capabilities.\n\nPredictive Intelligence Development\nTranslate confirmed root cause investigations, reliability analyses, operational learning, and equipment performance trends into predictive monitoring strategies that prevent recurrence of failures.\n\nBuild and maintain the engineering knowledge base of confirmed failure modes, leading indicators, detection thresholds, probable causes, engineering assumptions, and recommended field responses.\n\nAnalyze fleet performance, equipment downtime, and operational events to identify recurring failure mechanisms and prioritize opportunities for predictive monitoring.\n\nDevelop engineering approaches for time-series analysis that characterize how degradation develops over time across major equipment systems.\n\nAuthor detection rule specifications that define how abnormal operating behavior should be identified while partnering with Data Science teams to translate those specifications into predictive analytics applications.\n\nContinuously expand predictive monitoring coverage across fleet systems by identifying new opportunities to detect failures earlier and improve operational reliability.\n\nEstablish governance processes that ensure confirmed root cause investigations, operational lessons learned, and reliability improvements are systematically incorporated into the organization’s monitoring standards, detection rules, and engineering knowledge base.\n\nContinuously improve the Rules Library by validating existing detection logic against operational outcomes and incorporating new failure signatures as they are discovered across the fleet.\n\nPredictive Alert Architecture & Operational Decision Support\nDefine the engineering specifications for predictive alerts, ensuring every alert provides sufficient operational context-including supporting trend information, probable causes, recommended response actions, and expected operational outcomes-to enable informed decision-making rather than simply notifying users of abnormal conditions.\n\nDesign alert thresholds and notification strategies that maximize actionable early warning while minimizing false positives and operational fatigue.\n\nDefine escalation architectures that ensure the appropriate personnel receive the right information at the right time based on severity, operational risk, and business impact.\n\nLead the deployment of new predictive monitoring capabilities by developing communication plans, response guidance, and training materials that enable Operations, Maintenance, and Technical Support teams to confidently interpret and respond to predictive alerts.\n\nDevelop and maintain engineering metrics that measure alert effectiveness, intervention success, operational outcomes, and monitoring system performance.\n\nConduct systematic reviews of monitoring effectiveness, refining detection logic, thresholds, and alert strategies based on operational feedback and measured results.\n\nFleet Intelligence Products & Engineering Enablement\nDefine the engineering specifications for fleet health dashboards, operational bulletins, and decision-support products that provide field operations and technical support with structured visibility into equipment condition, emerging risks, and fleet-wide reliability trends.\n\nDefine the engineering specifications for standardized fleet health reporting products-including operational summaries, recurring trend reports, and fleet reliability analyses-that enable proactive maintenance planning and operational decision-making.\n\nDesign standardized alert response packages that provide field personnel and remote support teams with the technical information, historical context, probable causes, recommended first-response actions, and expected resolution criteria necessary to resolve predictive alerts without requiring engineering intervention.\n\nPartner with Digital Solutions teams to deliver fleet intelligence through enterprise dashboards, mobile applications, and other digital platforms.\n\nEstablish engineering standards, governance processes, and best practices that enable scalable, repeatable fleet health monitoring across the organization.\n\nQualifications Required\nBachelor’s degree in Mechanical Engineering, Electrical Engineering, Controls Engineering, Systems Engineering, Petroleum Engineering, or a related engineering discipline.\n\nEight (8) or more years of experience in systems engineering, reliability engineering, industrial controls, automation, predictive maintenance, asset performance management, or complex industrial systems.\n\nExperience working with large-scale industrial equipment in asset-intensive industries such as drilling, mining, heavy equipment, manufacturing, marine, rail, power generation, or similar environments.\n\nStrong understanding of industrial control systems, instrumentation, condition monitoring technologies, and operational data platforms.\n\nExperience working with industrial historians, SCADA systems, PLC-based equipment, or time-series operational data.\n\nWorking knowledge of Root Cause Analysis (RCA), Failure Modes and Effects Analysis (FMEA), reliability engineering, and predictive maintenance methodologies.\n\nDemonstrated experience developing engineering standards, technical specifications, system requirements, monitoring strategies, or equipment health frameworks.\n\nExperience collaborating with software engineering, digital product, or data science teams to deliver industrial monitoring or predictive analytics solutions.\n\nPreferred\nExperience designing predictive maintenance or condition monitoring programs for complex industrial assets.\n\nFamiliarity with machine learning, industrial analytics, digital twins, or asset performance management platforms.\n\nKnowledge of industrial networking, automation platforms, fleet management systems, and equipment health monitoring technologies.\n\nExperience defining engineering requirements for digital products or enterprise monitoring systems.\n\nStrong technical writing, analytical reasoning, and systems thinking skills.\n\nExcellent communication and stakeholder management abilities with experience influencing cross-functional engineering organizations.\n\nAdditional Details:\nThis position requires the person to 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. The Engineer must work with an emphasis on planning, multitasking, and prioritization to maximize efficiency of the team. Must be able to work closely with others and manage customer interaction in a professional manner. 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).","description_format":"text","description_chars":11771,"description_truncated":false,"requirements":{"experience_years_min":8,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Petroleum & Mining Engineering","Oil & Gas"],"lifecycle":[{"event":"open","at":"2026-10-04T03:53:26Z"}],"visa":[],"liveness":{"score":11,"band":"cold","label":"Long shot","p_open":1,"p_active":0.375,"p_room":0.28,"age_days":81,"expected_fill_days":28,"reasons":["conf:2","stale_co","velocity","win:tail","crowd:brand"],"computed_at":"2026-10-13T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/patenergy-senior-systems-engineer-predictive-fleet-intelligence","json_url":"https://alion.io/job/patenergy-senior-systems-engineer-predictive-fleet-intelligence.json","meta":{"generated_at":"2026-10-13T21:19:55Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":32709,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-14T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":2504637},"rest":"https://alion.io/mcp/rest/get_company?id=2504637"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fpatenergy-senior-systems-engineer-predictive-fleet-intelligence"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fpatenergy-senior-systems-engineer-predictive-fleet-intelligence"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fpatenergy-senior-systems-engineer-predictive-fleet-intelligence"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/patenergy-senior-systems-engineer-predictive-fleet-intelligence\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fpatenergy-senior-systems-engineer-predictive-fleet-intelligence"}]}