Reliability Engineer-IIoT & Connected Assets

HalliburtonHouston, TX
Onsite

About The Position

We are scaling our IIoT and connected-maintenance product into new product lines and expansion projects, and we need a reliability engineer who can lead that technical growth. The role is built around understanding why equipment fails — mechanically and electronically — and translating that understanding into the right technology to measure, detect, and prevent those failures. The engineer moves fluidly between the desk, the bench, and the field: reading drawings and manuals to understand the equipment and process, analyzing failure mechanisms to find true root cause, getting hands-on to build and test prototypes, and proving the value of solutions with data and a sound business case. A core part of the role is choosing the correct sensors for industrial process and equipment measurement, writing their technical specifications, testing them on prototypes, and relating the resulting readings to the algorithms that detect failures early enough to prevent them. This person owns the technical discovery-to-pilot loop — running failure-mode analysis, selecting detection technologies, and building and field-testing prototypes as proofs of concept inside the IIoT product, then translating validated findings into a development roadmap. They work in an agile team, one of several reliability engineers each focused on a different product line but sharing the same approach, with the autonomy to research, propose, pilot, and present solutions, and regular exposure to cross-functional teams and management.

Requirements

  • Bachelor’s degree in Electronics, Electrical, or Mechanical Engineering (or closely related field). Equivalent practical experience will be considered.
  • 5+ years in reliability, maintenance, failure analysis, test, or equipment/instrumentation engineering.
  • Working understanding of both mechanical and electronic failure mechanisms and how they progress.
  • Hands-on experience running FMEA / FMECA and root-cause analysis on physical equipment.
  • Practical knowledge of sensors for process and equipment measurement in industrial environments — selecting the correct sensors, writing technical specifications, testing on prototypes, and relating readings to failure-detection logic.
  • Able to build, wire, and test electronic and sensor prototypes — not only specify them on paper.
  • Self-directed — able to scope, research, propose, run, and report on work with limited supervision, while contributing as part of a team.
  • Based in Houston, on-site, and willing/able to travel to equipment and shop locations.
  • Reliability, maintainability, availability & risk management (RAM); failure analysis / root cause; FMEA / FMECA; reliability block diagrams; Weibull analysis; tribology.
  • Sensors for process and equipment measurement in industrial environments; sensor selection; technical specification writing; bench and prototype testing; relating readings to failure-detection algorithms.
  • Hydraulic systems, lubrication systems, oil condition monitoring, fluid analysis, vibration analysis, thermal monitoring, and failure detection techniques.
  • Control systems, SCADA, PLCs, and closed control loops; industrial communication protocols (CAN bus / J1939, MQTT, OPC, Modbus).
  • Condition-based, preventive, run-to-failure, and failure-finding strategies; condition-monitoring techniques; asset management.
  • Digital transformation / machine learning / Industry 4.0; business intelligence (e.g., Power BI); data extraction and analysis.
  • Life-cycle cost; financial analysis for business cases (TCO, NPV, ROI, IRR, cost Pareto and trending).
  • SAP (PM module); project management; agile ways of working; management of change; operations and equipment knowledge across PSLs.
  • HSE basics and safe driving; continuous-improvement certification (e.g., CI Bronze / Red level).

Nice To Haves

  • Embedded/electronics prototyping depth: microcontrollers, data loggers, edge devices, wiring, and sensor integration.
  • Experience in industrial, heavy-equipment, or rotating-equipment environments, hydraulic power units, pumps, engines, including control systems and industrial networks.
  • Experience selecting, specifying, and deploying instrumentation in hazardous locations, including Class I Div 2, ATEX, and IECEx environments.

Responsibilities

  • Understand the equipment, systems, and process: Read and interpret mechanical, electrical/electronic, hydraulic, and P&I drawings, OEM service manuals, and specifications. Develop a working understanding of how assets and their sub-systems function within their operating conditions and surrounding process. Assess equipment criticality to focus reliability effort where it delivers the most value.
  • Investigate failures and determine root cause: Lead and review failure-mode analysis (FMEA / FMECA) — including analyses produced by the reliability team — and root-cause analysis across mechanical and electronic failure mechanisms. Engage internal and external technology teams, vendors, and subject-matter experts to determine failure mechanisms. Characterize each failure mechanism — how it develops, its measurable symptoms, and the lead time to act — and define how data can be used to identify and prevent it.
  • Research detection technology and select sensors: Research and benchmark sensing, monitoring, and diagnostic technologies against each failure mechanism — vibration, oil quality/condition, temperature, pressure, flow, electrical signals/signature, acoustic, and equipment-bus data. Choose the correct sensors for process and equipment measurement in industrial environments; define what to measure, where, and the measurement technique. Select instrumentation and signal types (e.g., 4–20 mA, 0–5 V / 0.5–4.5 V, RTD/thermocouple, digital I/O, CAN / J1939) and define alert/alarm criteria. Write the technical specifications for sensors and instrumentation. Define diagnosis and prognosis logic and health-scoring inputs that detect deviations early, balancing detection confidence against false alarms.
  • Build prototypes, run pilots and PoCs: Propose hypotheses and validate them with data; specify, source, wire, and assemble sensor kits, edge hardware, and electronic prototypes. Test sensors on prototypes and validate the quality of their readings. Get hands-on and "feet in the mud" — install, instrument, and test on real equipment in the lab, shop, and field; capture and validate data quality. Design and run pilots and PoCs end-to-end with clear success criteria; measure results and iterate. Account for field reality throughout: hazardous-area constraints, ruggedization, packaging/enclosures, connectivity, and serviceability.
  • Integrate with the IIoT product and shape the roadmap: Work as part of the team — with the IIoT Product Manager, technology, and development teams — to integrate validated sensors and prototypes into the current IIoT solution across the Detect – Design – Deploy cycle. Relate sensor readings to failure-detection logic and hand PoC results to the development team to build new monitoring algorithms. Propose validated use cases and partner with the Product Manager to agree on a prioritized development roadmap. Engage software/architecture developers, SMEs, and OEM/sensor vendors to align technical decisions and unblock execution.
  • Organize and standardize failure data: Organize failure data and build a standardized failure database. Document findings, designs, and standards (sensor selection, install standards, health logic by sub-system) so they scale across equipment types and product lines. Extract and leverage the right data — for the right reasons — to support detection, prevention, and decisions.
  • Drive KPIs, deployment, and stakeholder engagement: Engage product-line and area operations leaders through weekly meetings to drive the deviation / anomaly review process. Propose and track KPIs to measure reliability improvement and program success. Lead technology deployment within the area, including stakeholder communication and end-user training. Plan and deliver work in an agile cadence as part of the reliability team.
  • Build business cases and lifecycle / cost reporting: Produce equipment life and reliability reports and total-cost-of-ownership (TCO) analyses. Build business cases (e.g., life-cycle cost, NPV, ROI) to justify and fund the development of technology solutions. Present findings, prototype results, and recommendations clearly to peers and management.

Benefits

  • Comprehensive and affordable benefits package
  • Support for physical, emotional, financial and parental needs
  • Access to a wide range of resources designed to help you thrive at work and at home
© 2026 Teal Labs, Inc
Privacy PolicyTerms of Service