AI Engineer
- Kolkata, West Bengal
- Permanent
- Full-time
- Identify the Process to Automate
- Look for repetitive, rule-based, or data-heavy tasks.
- Examples: invoice processing, customer support queries, recruitment screening, demand forecasting.
- Analyze & Map the Workflow
- Break the process into input → action → output.
- Understand which parts need human judgment and which can be automated.
- Choose the Right AI Technique
- NLP (Natural Language Processing): For text, emails, chatbots, resume screening, sentiment analysis.
- Computer Vision: For image/video processing, quality inspection, ID verification.
- Machine Learning: For predictions, risk scoring, personalization, forecasting.
- Collect & Prepare Data
- AI relies on quality data (historical records, documents, transactions).
- Clean and label data for training models if needed.
- Build or Integrate AI Models
- Train custom models (using Python, TensorFlow, PyTorch, etc.)
- Or integrate ready-made AI tools (like UiPath AI Center, Microsoft Power Automate, OpenAI APIs, AWS AI services).
- Integrate with Existing Systems
- Connect AI models with ERP, CRM, HRMS, or other enterprise systems through APIs or RPA bots.
- Test & Monitor
- Start with a pilot run.
- Monitor accuracy, efficiency, and user adoption.
- Continuously retrain or fine-tune AI models.
- Scale & Optimize
- Once stable, roll out automation across departments.
- Add dashboards for monitoring KPIs (cost savings, time reduction, error reduction).