AI-Enabled Plant Head

Santriya Technologies; Chennai District; On-site; INR 3,000,000 - 6,000,000; Part time

Job summary

Santriya Technologies seeks an AI-Enabled Plant Head to own safe, reliable and cost-effective plant performance, leveraging AI-powered planning, maintenance, quality, and operational intelligence while maintaining clear human accountability. You will manage production, maintenance, quality, EHS, cost and delivery at the site.

Role requires using integrated dashboards and AI analytics to identify bottlenecks, failure risk, yield loss and capacity opportunities, while ensuring governance and

Qualifications

• Lead production/service, maintenance, quality, EHS and cost performance for the site.
• Use AI analytics to identify bottlenecks and opportunities.
• Ensure governance, safety and accountability in AI-enabled decision making.

Responsibilities

• Own site performance across production, maintenance, quality, EHS and delivery.
• Leverage AI dashboards to improve OEE, throughput and costs.
• Set operating rhythms, escalation thresholds and cross-functional action plans.

Skills

Leadership

AI literacy

Operations management

Data analytics

Tools

AI tools

Job description

• Santriya Technologies is seeking an AI-Enabled Plant Head to own safe, reliable and cost-effective plant or large facility performance, using AI-enabled planning, maintenance, quality and operational intelligence while retaining clear human accountability.
• 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 escalate conflicts or missing guidance.
• Do not invent product features, prices, customer entitlements, engineering limits, regulatory positions or safety instructions.

Key Responsibilities:

• Own production/service, maintenance, quality, EHS, people, cost and delivery performance for the site.
• Use integrated dashboards and AI analytics to identify bottlenecks, failure risk, yield loss, energy waste and capacity opportunities.
• Challenge model recommendations against operating constraints, safety limits and product/customer requirements before approval.
• Set daily/weekly operating rhythms, escalation thresholds and cross-functional action plans.
• Drive OEE, throughput, reliability, right-first-time, inventory and cost improvement programs.
• Ensure maintenance, engineering changes, permits, quality holds and deviations follow documented governance.
• Build leadership capability and AI literacy across supervisors and engineers.
• Own business continuity, critical spares, contractor strategy and major incident response.
• 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:
• Safety, service and quality targets are sustained
• OEE/throughput and cost performance improve
• Unplanned downtime and chronic losses reduce
• Decisions remain controlled, documented and auditable