AI-Enabled Environmental, Health & Safety Engineer

• Santriya Technologies is seeking an AI-Enabled Environmental, Health & Safety Engineer to strengthen workplace safety and environmental performance using AI-assisted trend analysis, inspections and knowledge retrieval, with all safety decisions governed by approved standards and competent human judgement.
• 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:

• Maintain risk assessments, legal registers, permits, inspections, emergency plans and EHS procedures.
• Use AI analytics to detect incident trends, unsafe-condition patterns and leading indicators from verified records.
• Conduct site inspections, audits and task observations; never substitute AI analysis for physical verification.
• Lead incident investigation, root-cause analysis and corrective/preventive action tracking.
• Support contractor safety, LOTO, work-at-height, fire, material handling and warehouse/plant safety controls.
• Monitor waste, emissions, energy or environmental obligations relevant to the site.
• Train teams using current product/equipment manuals and approved safety content.
• Escalate critical risks immediately and preserve stop-work authority.
• 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:
• Recordable incidents and repeat findings reduce
• Corrective actions close on time
• Leading safety indicators improve
• Regulatory and audit readiness remains strong