AI Engineer

AI Solution Development
• Design, develop, and implement AI-based document digitization solutions.
• Build intelligent document processing (IDP) workflows for enterprise applications.
• Configure, train, and optimize document classification and data extraction models.
• Develop automated validation workflows and business rule engines.
• Analyze AI model performance and continuously improve model accuracy.
• Support deployment, monitoring, and lifecycle management of AI solutions.
Generative AI & Agentic AI
• Design and implement Generative AI and Agentic AI solutions.
• Build AI agents using frameworks such as ADK, LangGraph, and CrewAI.
• Develop Retrieval-Augmented Generation (RAG) solutions and intelligent workflows.
• Perform prompt engineering and fine-tuning of Large Language Models (LLMs) for domain-specific use cases.
• Optimize AI models for enterprise-scale performance and accuracy.
Full Stack AI Development
• Develop backend services using Python.
• Build frontend applications using React or other modern JavaScript frameworks.
• Develop RESTful APIs and integrate AI services with enterprise applications.
• Ensure secure and scalable AI application architecture.
Cloud & MLOps
• Deploy AI applications on AWS, Azure, or Google Cloud Platform (GCP).
• Build CI/CD pipelines for AI/ML model deployment.
• Implement MLOps best practices for model versioning, monitoring, retraining, and governance.
• Monitor cloud infrastructure and optimize performance, scalability, and cost.
Integration & Collaboration
• Integrate AI services with Enterprise Resource Management (ERM) systems and supporting applications.
• Collaborate with Product Owners, Business Analysts, Architects, and QA teams throughout the development lifecycle.
• Prepare technical documentation, architecture diagrams, and deployment guides.
• Participate in Agile/Scrum ceremonies and provide technical leadership.