Senior Full-Stack Engineer | AI / LLM / RAG

Contributed to the core AI-enabled enterprise SaaS product, building backend services in Python / .NET, REST APIs, and data processing pipelines to support privacy-safe consumer/enterprise intelligence features. Implemented data ingestion and transformation workflows from diverse sources, ensuring data privacy and compliance across multi-tenant clients, using secure AWS infrastructure and PostgreSQL/DynamoDB/S3. Collaborated with data-science and ML teams to productionize machine learning models, including data preprocessing, feature extraction, and batch inference pipelines. Built authentication/authorization layers with role-based access control (RBAC) and secure SSO features for enterprise clients handling sensitive data. Established CI/CD pipelines, containerized deployments (Docker, Kubernetes), and observability solutions for reliability and scalability in production. Participated in architecture reviews and mentored junior engineers, helping integrate privacy-by-design principles throughout backend and data-processing layers.

Contributed to end-to-end development of WATI’s multi-tenant messaging/CRM platform, building backend services with Node.js/Express, MongoDB/Redis, and handling message routing, multi-agent inboxes, and workflow automation on the WhatsApp Business API. Built real-time chat and support dashboards with React + Tailwind CSS, enabling agents to manage customer conversations, view engagement metrics, and handle support at scale. Integrated automation tools and chatbot logic using RAG, LLM and vector DB to support auto-replies, templated messages, and broadcast campaigns — improving response speed and support throughput. Implemented secure authentication and authorization, multi-tenant data isolation, ensuring separation of data between different business clients. Set up containerized deployment (Docker, possibly Kubernetes, AWS ECS), CI/CD pipelines, monitoring, and logging to support platform scalability and reliability as client base grew. Optimized message-processing pipelines and database usage to handle high concurrency and large numbers of customers/messages, reducing latency and improving throughput under load.

Built backend services and secure REST APIs to support Micro Connect’s financing and revenue-sharing platform, managing user data, transaction flows, loan/obligation tracking, and payment settlement using Python/Django, PostgreSQL, and AWS. Developed business-logic for structured financial products, handling repayment scheduling, revenue tracking, risk assessment data pipelines, and investor-facing API endpoints. Implemented authentication, authorization, data encryption, compliance logging, and audit trails to satisfy regulatory & financial data security requirements. Built internal dashboards and admin tools for operations teams to monitor investments, business performance, risk metrics, user account statuses, and financial flows using web frontend (React). Designed database schema, indexing, and caching (Redis) to support high concurrency and efficient query performance under financial-transaction loads. Introduced CI/CD workflows, containerization, and cloud deployment to enable scalable and maintainable infrastructure, supporting growth of client base and transaction volume.

Assisted the engineering team in developing backend services for the fintech platform using Python/Django and PostgreSQL. Implemented basic REST API endpoints for transaction tracking and reporting. Supported data validation, testing, and documentation for compliance workflows. Collaborated with senior engineers in a small team of 3–4 developers, participated in daily standups, and learned company coding standards and secure development practices.