Reliability Head

We are looking for an experienced Reliability Head to lead Asset Reliability and Predictive Maintenance initiatives across Process Industries and Renewable Power. The role will be responsible for developing and delivering reliability enhancement and predictive maintenance solutions by combining deep engineering and equipment expertise with AI/ML and Generative AI technologies.

The ideal candidate should have strong experience in maintenance reliability engineering, Failure Mode and Effects Analysis (FMEA), Condition-Based Maintenance (CBM), Predictive Maintenance (PdM), Root Cause Analysis (RCA) and asset health monitoring, along with a strong understanding of rotating and static equipment.

You will work closely with clients, reliability engineers, and AI/ML teams to identify equipment failure modes, assess equipment health, validate predictive models, and recommend actionable measures to improve asset performance and reliability.

Key Responsibilities

• Lead Asset Reliability, Reliability Engineering and Predictive Maintenance initiatives for process industries and renewable power assets.
• Provide technical leadership for reliability enhancement and predictive maintenance solutions for global clients.
• Apply extensive knowledge of rotating and static equipment to identify potential failure modes and equipment health indicators.
• Lead FMEA, Asset Criticality, Reliability-Based Maintenance (RBM), RCA, CBM and PdM activities.
• Review customer sensor tags, equipment data, engineering documents and other relevant information required for reliability analysis.
• Develop and validate equipment ontology, component structures, operating parameters and failure modes.
• Work closely with AI/ML and GenAI teams to explain equipment behaviour, operational conditions and failure mechanisms.
• Review features and inputs used for AI/ML model development and provide engineering and reliability feedback.
• Review outputs generated by AI/ML models and GenAI agents and validate the results from an engineering and reliability perspective.
• Lead identification of equipment failure modes and establish relationships between components, operating parameters and potential failures.
• Support identification of the root cause of functional failures and recommend appropriate corrective and preventive actions.
• Lead technical discussions with clients and internal teams during project execution.
• Identify opportunities to detect anomalies, predict equipment health and prevent failures before they occur.
• Recommend appropriate reliability and maintenance strategies based on equipment condition and failure patterns.
• Provide technical guidance on various Condition Monitoring and Predictive Maintenance techniques.
• Lead and mentor a team of reliability engineers and ensure effective execution of reliability initiatives.
• Collaborate with cross-functional teams to deliver high-quality reliability and predictive maintenance solutions.

Core Technical Skills

• Asset Reliability / Reliability Engineering
• Predictive Maintenance (PdM)
• Condition-Based Maintenance (CBM)
• Failure Mode and Effects Analysis (FMEA)
• Reliability-Based Maintenance (RBM)
• Asset Criticality Assessment
• Root Cause Analysis (RCA)
• Rotating & Static Equipment
• Plant Maintenance / Plant Operations
• Equipment Health Monitoring
• Anomaly Detection
• Failure Mode Identification
• AI/ML & GenAI Applications in Asset Reliability

Condition Monitoring Expertise

Hands-on experience or strong knowledge of the following is preferred:

• Vibration Analysis
• Infrared Thermography
• Power Monitoring
• Oil Analysis
• Ultrasound Monitoring
• Sensor and equipment health monitoring

Relevant certifications in condition monitoring and reliability engineering will be an added advantage.

Preferred Industry Experience

Experience in one or more of the following environments will be highly desirable:

• Process Industries
• Renewable Power
• Manufacturing
• Power & Energy
• Industrial Plants
• Heavy Engineering
• Asset-Intensive Industries
• Plant Maintenance & Operations

Education

• BS / B.Tech / B.E. in Engineering, preferably Mechanical Engineering
• MS / M.Tech / M.E. in Mechanical, Reliability, Maintenance or a related engineering discipline is preferred.
• Candidates from Tier 1 or Tier 2 institutes preferred.

What We're Looking For

• 10+ years of relevant experience in reliability engineering, maintenance, predictive maintenance or plant operations.
• Strong understanding of industrial equipment and equipment failure mechanisms.
• Proven experience in FMEA, RCA, RBM, Asset Criticality, CBM and PdM.
• Ability to translate complex equipment and engineering concepts into actionable reliability strategies.
• Experience working with technical, engineering and AI/ML teams.
• Strong client-facing and technical communication skills.
• Demonstrated ability to lead teams and manage technical discussions.
• Analytical mindset with the ability to interpret equipment data and identify potential failure patterns.
• Strong problem-solving and decision-making capabilities.

Why This Role

This is an opportunity to play a key leadership role at the intersection of Engineering, Asset Reliability, Predictive Maintenance, AI/ML and GenAI. You will work on complex industrial reliability challenges, collaborate with global clients and multidisciplinary teams, and contribute to solutions designed to improve equipment performance, reduce unplanned failures and enhance asset reliability.