• Designed the AI-enabled architecture for transforming Tivhi Play into an intelligent, personalized content engagement and earning platform.
• Designed Agentic AI workflows using LangChain and LangGraph for content intelligence, recommendation, automation, and user engagement use cases.
• Integrated Ollama and private LLMs for secure and controlled execution of AI workloads.
• Designed RAG pipelines combining content ingestion, chunking, embeddings, vector search, retrieval, reranking, and LLM-based response generation.
• Implemented AI-powered content recommendation using user behavior, preferences, content metadata, engagement history, and contextual signals.
• Developed AI workflows for content classification, categorization, metadata extraction, summarization, tagging, semantic search, and content discovery.
• Designed AI agents capable of orchestrating multiple tools, APIs, databases, and content services to automate end-to-end workflows.
• Explored and implemented Model Context Protocol (MCP) to enable AI agents to securely interact with tools, APIs, data sources, and platform services.
• Developed AI microservices using Python and FastAPI for model inference, recommendation services, RAG services, content intelligence, and agent orchestration.
• Implemented LLMOps practices covering model lifecycle management, prompt/version management, evaluation, monitoring, observability, performance tracking, and continuous improvement.
• Worked on LLM fine-tuning and model optimization for domain-specific content understanding and recommendation use cases.

Azure AI Foundry & Azure Cloud:

• Utilized Azure AI Foundry to experiment with, evaluate, manage, and integrate foundation/LLM models for Tivhi Play’s AI-powered content intelligence and recommendation capabilities.
• Implemented Azure AI Foundry-based generative AI workflows for content summarization, classification, metadata enrichment, and personalized content experiences.
• Leveraged Azure AI Foundry model evaluation and prompt experimentation to test AI responses, improve prompt quality, and optimize domain-specific AI workflows.
• Integrated Azure-hosted AI services with LangChain, LangGraph, Python, FastAPI, and RAG pipelines to build scalable agentic AI capabilities.
• Utilized Azure Cloud resources for hosting backend/API services, AI workloads, application components, storage, monitoring, and scalable platform infrastructure.
• Designed cloud-based integration between Azure services, AI agents, LLMs, databases, APIs, and the Tivhi Play Android/eWeb applications.
• Applied Azure cloud capabilities for scalability, security, monitoring, logging, deployment, and production operations.
• Implemented secure communication between cloud-hosted services and Tivhi Play’s mobile, web, backend, and AI components.

Mobile & Web Development:

• Designed and developed the Tivhi eWeb Dashboard using a full-stack architecture with Python, Next.js, and TypeScript.
• Developed dashboard modules for content management, user engagement, analytics, platform monitoring, and administrative operations.
• Designed and integrated REST APIs between the Tivhi Play Android application, eWeb dashboard, backend services, and AI services.
• Implemented Android API communication using Retrofit and Volley for efficient content retrieval, recommendations, user activity, and dynamic application data.
• Designed and implemented a custom hybrid nested horizontal/vertical scrollable RecyclerView architecture for the Tivhi Play home page.
• Built dynamic content sections supporting multiple horizontal carousels within a vertically scrolling feed for a rich and scalable social-content experience.
• Implemented dynamic home-page rendering for personalized content, recommendations, trending content, social presence, advertisements, and engagement modules.
• Optimized RecyclerView performance, view recycling, API loading, pagination, caching, and smooth scrolling.

Backend, APIs & Content Platform:

• Designed scalable ASP.NET Core and FastAPI services integrating traditional backend capabilities with AI/LLM services.
• Developed APIs for user management, content delivery, recommendations, engagement tracking, rewards, analytics, and third-party integrations.
• Developed and integrated the Global Movies Importer API for automated movie content ingestion, classification, metadata processing, enrichment, and content discovery.
• Built intelligent content pipelines combining APIs, databases, AI models, RAG, and agentic workflows.
• Integrated AI capabilities with Watch-to-Earn, Refer-and-Earn, Rewards, Streaks, Gamification, and Advertisement modules.
• Collaborated with data science, backend, Android, frontend, and product teams to integrate AI capabilities across the platform.
• Focused on scalability, security, reliability, observability, performance optimization, and cost optimization across mobile, web, backend, AI, and cloud services.