AI ML Engineer

Key Responsibilities

• Lead\ AI Automation Projects
  
  • Drive\ end\-to\-end implementation of AI\-based automation workflows for data\ extraction, cleansing, and enrichment .
    
  • Translate\ business requirements into scalable AI\/ML and automation solutions.
    
  • GenAI\ & LLM Development
    
    • Build,\ fine\-tune, and deploy Generative AI and LLM models (OpenAI, LLaMA,\ Mistral, DeepSeek, etc.) for domain\-specific use cases.
      
    • Implement prompt engineering, RAG (Retrieval\-Augmented Generation) , and custom\ model training for enhanced performance.
      
    • Automation\ & Workflow Design
      
      • Architect\ and maintain automation pipelines for structured and unstructured\ data extraction (from text, documents, PDFs, websites, APIs).
        
      • Integrate RPA tools, APIs, and AI\-driven agents for intelligent workflow\ orchestration.
        
      • Data\ Management
        
        • Design\ efficient workflows for data ingestion, validation, transformation,\ and quality control .
          
        • Collaborate\ with data engineering teams to ensure high\-quality, clean datasets for downstream AI\/analytics.
          
        • Leadership\ & Collaboration
          
          • Provide technical leadership and mentor junior engineers in AI\/automation\ best practices.
            
          • Collaborate\ with prod
            
          • uct,\ business, and engineering teams to identify opportunities for AI\-driven\ efficiency.
            
            
            
            Requirements

            We are seeking a highly skilled AI Automation Lead with hands\-on expertise in Generative AI (GenAI), Large Language Models\ (LLMs), DeepSeek, and intelligent automation workflows . The ideal candidate will lead the design, development, and\ deployment of AI\-driven automation pipelines for large\-scale data\ extraction, processing, and enrichment . This role requires both technical expertise and leadership\ skills , as you will be working closely with data engineers, analysts, and\ business stakeholders to deliver scalable AI\-powered automation solutions.
            

            
            

            
            

            • Prior\ experience in SaaS or platform environments .
              
            • Exposure\ to MLOps, scalable LLM deployment, and API\-first architectures .
              
            • Understanding\ of enterprise compliance & risk frameworks .
              
            • Experience\ leading AI teams