My name is Orina Tolulope, I am excited to apply for the AI Engineer position at your prestigious organization. I have worked on several projects that involve building full-stack applications. Two notable products that I had the opportunity to lead and contribute to are Customer Support Assistant, a generative AI-powered virtual assistant, helps streamline customer self-service processes and reduce operational costs by automating responses for customer service queries. This product was built with AWS' flagship omnichannel contact center, Amazon Connect, and their agentic AI service, Amazon Q. Following standard product development best practices, I started out with defining an architectural vision that connects to the business challenge and problem of improving customer service support and efficiently responding to customer queries. I also looked into the niche for which we are building a support assistant; in this case it was for our organization, a technology consulting and software integration organization. I went on to produce a baseline architecture for the product, gathering test data and FAQs to start out the build of an MVP. Afterwards, I went on to identify an opportunity with Amazon Connect Chat, which allows customers to start a chat with an agent (Amazon Q in Connect agent), step away from it, and then resume the conversation. Today, this Customer Support Assistant helps us effectively understand our users' queries, streamline business processes and interactions with our IT helpdesk support team, hand off chats to available support engineers, and improve overall turnover by around a 20% increase. CecureStream is an AI-powered video conferencing application. On this product, I led a team of over seven (7) engineers and architects providing architectural insight and vision, right from the building of the MVP to the fully fledged, multi-featured product that CecureStream is today. I, in conjunction with the team, started off with the design of the business, solution, data, and software architectures, which serve as layouts and blueprints with which we build. Afterwards, we started out building its moving parts, including deployment of the base infrastructure, then its respective core features, including authentication/authorization (using Amazon Cognito), developing APIs, and its backend layers that enable functionality and business logic, primarily using serverless services (API Gateway, AWS Lambda, AWS Chime SDK, amongst others). I recently added the AI feature, a live meeting assistant, to the application that serves to support attendees and participants to gather insights using the Agent…My name is Orina Tolulope, I am excited to apply for the AI Engineer position at your prestigious organization. I have worked on several projects that involve building full-stack applications. Two notable products that I had the opportunity to lead and contribute to are Customer Support Assistant, a generative AI-powered virtual assistant, helps streamline customer self-service processes and reduce operational costs by automating responses for customer service queries. This product was built with AWS' flagship omnichannel contact center, Amazon Connect, and their agentic AI service, Amazon Q. Following standard product development best practices, I started out with defining an architectural vision that connects to the business challenge and problem of improving customer service support and efficiently responding to customer queries. I also looked into the niche for which we are building a support assistant; in this case it was for our organization, a technology consulting and software integration organization. I went on to produce a baseline architecture for the product, gathering test data and FAQs to start out the build of an MVP. Afterwards, I went on to identify an opportunity with Amazon Connect Chat, which allows customers to start a chat with an agent (Amazon Q in Connect agent), step away from it, and then resume the conversation. Today, this Customer Support Assistant helps us effectively understand our users' queries, streamline business processes and interactions with our IT helpdesk support team, hand off chats to available support engineers, and improve overall turnover by around a 20% increase. CecureStream is an AI-powered video conferencing application. On this product, I led a team of over seven (7) engineers and architects providing architectural insight and vision, right from the building of the MVP to the fully fledged, multi-featured product that CecureStream is today. I, in conjunction with the team, started off with the design of the business, solution, data, and software architectures, which serve as layouts and blueprints with which we build. Afterwards, we started out building its moving parts, including deployment of the base infrastructure, then its respective core features, including authentication/authorization (using Amazon Cognito), developing APIs, and its backend layers that enable functionality and business logic, primarily using serverless services (API Gateway, AWS Lambda, AWS Chime SDK, amongst others). I recently added the AI feature, a live meeting assistant, to the application that serves to support attendees and participants to gather insights using the AgentWWWW…