AI-Enabled Warehouse Supervisor

Santriya Technologies; Chennai; On-site; INR 450,000 - 550,000; Full time

Job summary

Santriya Technologies is seeking an AI-Enabled Warehouse Supervisor to lead shift-level warehouse execution across receiving, put-away, picking, packing, sortation and dispatch using AI-assisted workload, labor and flow insights. You will oversee start-up, staffing and workload priorities, using WMS and AI forecasts to anticipate volume and labor needs while ensuring SOP compliance and safety.

The role requires hands-on coaching, real-time monitoring and precise record-keeping to drive

Responsibilities

• Run shift start-up, staffing, area allocation and workload priorities against service commitments.
• Use WMS and AI forecasts to anticipate volume, congestion and labor needs, adjusting with supervisor judgement.
• Monitor productivity, quality, backlog, equipment status and safety in real time.
• Ensure associates follow SOPs for product handling, scanning, packaging, hazardous/high-value items and exceptions.
• Coordinate automation, maintenance and IT support when systems or material-handling equipment degrade.
• Investigate misses, damage, mis-picks and process deviations and implement corrective actions.
• Coach team leaders and associates using objective performance and quality data.
• Maintain accurate handover, incident and shift records.

Job description

Job Summary

Santriya Technologies is seeking an AI-Enabled Warehouse Supervisor to lead shift-level warehouse execution across receiving, put-away, picking, packing, sortation and dispatch using AI-assisted workload, labor and flow insights.

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 escalation conflicts or missing guidance. Do not invent product features, prices, customer entitlements, engineering limits, regulatory positions or safety instructions.

Key Responsibilities

• Run shift start-up, staffing, area allocation and workload priorities against service commitments.
• Use WMS and AI forecasts to anticipate volume, congestion and labor needs, adjusting with supervisor judgement.
• Monitor productivity, quality, backlog, equipment status and safety in real time.
• Ensure associates follow SOPs for product handling, scanning, packaging, hazardous/high-value items and exceptions.
• Coordinate automation, maintenance and IT support when systems or material-handling equipment degrade.
• Investigate misses, damage, mis-picks and process deviations and implement corrective actions.
• Coach team leaders and associates using objective performance and quality data.
• Maintain accurate handover, incident and shift records.

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

• Throughput and SLA attainment improve
• Mis-picks/damage and safety incidents reduce
• Labour plan accuracy improves
• Automation downtime is escalated and recovered quickly