AI-Enabled Mechanical Maintenance Engineer

Santriya Technologies; Chennai District; On-site; INR 450,000 - 650,000; Full time

Job summary

Santriya Technologies is seeking an AI-Enabled Mechanical Maintenance Engineer to sustain mechanical assets and automated handling equipment using condition data and AI-supported diagnostics.

You will plan preventive, predictive and corrective maintenance for conveyors, lifts, pumps and HVAC, leveraging AI analytics to detect anomalies and drive improvements while maintaining strong safety and documentation standards.

Qualifications

• Plan preventive, predictive and corrective maintenance for conveyors and related equipment.
• Ability to use AI/analytics to detect anomalies and guide inspections.
• Experience with CMMS for work orders, spares, downtime codes and records.
• Strong root-cause analysis and corrective actions.
• Ensure safety, quality, privacy and data retention compliance.

Responsibilities

• Plan preventive, predictive and corrective maintenance for conveyors, lifts, pumps, HVAC and other equipment.
• Use AI/analytics to detect abnormal vibration, temperature, cycle time or failure patterns.
• Validate AI alerts with physical checks and maintenance history before intervention.
• Coordinate safe isolation, permits and contractor activities.
• Maintain manuals, lubrication plans and critical spares lists.
• Track MTBF/MTTR and drive continuous improvement.

Skills

AI analytics

CMMS usage

Root-cause analysis

Preventive maintenance

Vibration analysis

Tools

Diagnostics software

Industrial AI tools

Job description

• Santriya Technologies is seeking an AI-Enabled Mechanical Maintenance Engineer to maintain mechanical assets and automated material-handling equipment using condition data, AI-supported diagnostics and disciplined maintenance documentation.
• Product & documentation operating model: You will be assigned one or more company products, client solutions or operational services.
• The approved product documentation, SOPs, policies, process maps, knowledge articles, release notes, controls, scripts and AI runbooks are the source of truth.
• Use only approved enterprise AI tools to retrieve, summarize, draft, classify, prioritize or automate work.
• Validate material AI outputs against current documentation and authoritative system data, record exceptions, and escalated conflicts or missing guidance.
• Do not invent product features, prices, customer entitlements, engineering limits, regulatory positions or safety instructions.

Key Responsibilities:

• Plan preventive, predictive and corrective maintenance for conveyors, sorters, lifts, pumps, compressors, HVAC or assigned equipment.
• Use approved AI/analytics to detect abnormal vibration, temperature, cycle time or failure patterns and prioritize inspections.
• Validate AI alerts with physical checks, OEM limits and maintenance history before intervention.
• Manage work orders, spares, downtime codes, failure modes and completion evidence in CMMS.
• Lead breakdown troubleshooting, root-cause analysis and permanent corrective actions.
• Coordinate safe isolation, permits, contractors and return-to-service checks.
• Maintain equipment manuals, maintenance standards, lubrication plans and critical spares lists.
• Track MTBF, MTTR, availability and maintenance cost trends and drive continuous improvement.
• AI-enabled ways of working:
• Use approved GenAI copilots, enterprise search/RAG, analytics and workflow agents to reduce repetitive work and improve decision preparation.
• Keep prompts, outputs and automated actions within approved data-access, confidentiality and retention rules.
• Correct inaccurate summaries, classifications or recommendations before they become customer, operational or system records.
• Feed recurring AI errors, knowledge gaps and process friction into product, documentation and control improvement.
• Human accountability: AI is a copilot, not the accountable decision-maker.
• The role holder remains responsible for judgement, quality, privacy, security and appropriate escalation.
• Credit, fraud blocking, legal/regulatory, financial advice, safety-critical, clinical, employment and other high-impact decisions must follow delegated authority and required human review.

Success Measures:

• Asset uptime and MTBF increase
• Unplanned downtime and repeat failures reduce
• Maintenance plans become more predictive
• Safety and documentation compliance remain strong.