- Santriya Technologies is seeking an AI-Enabled Design Engineer to develop protected, manufacturable and maintainable designs using approved AI/generative design tools for option generation and review, with calculations and engineering approval remaining human-accountable.

- 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:

- Convert requirements and product/facility constraints into concepts, calculations, drawings, BOMs and specifications.

- Use AI/generative tools to explore alternatives, summarize constraints and flag potential issues, then validate using engineering methods.

- Perform design reviews, tolerance/interface checks, DFMEA and design-for-manufacture/assembly/maintenance assessments.

- Manage technical queries, design changes and revision-controlled documentation.

- Coordinate with procurement,



manufacturing, construction, quality and maintenance teams.

- Evaluate vendor data and component selections against approved requirements.

- Support prototype/site validation and capture lessons into standards.

- Protect proprietary drawings and technical data by using only approved AI environments.

- 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:
- Design cycle time improves without quality loss

- First-pass design approval improves

- Change/rework rates decline
- Design knowledge becomes reusable and controlled

📌 AI-Enabled Design Engineer (Chennai)
🏢 Santriya Technologies
📍 Chennai