Temitope O.

About Temitope O.

Software engineer with 4+ years at Amazon, specializing in AI tooling, cloud infrastructure, and developer experience. I build systems that make engineers more productive and customers more successful.At AWS, I pioneered internal adoption of Amazon Q and Kiro across my organization, designing agentic AI workflows that cut resolution time from hours to seconds and helped my team resolve tickets per month across 7–8 services. I built customer issue analysis systems used in executive business reviews (QBRs/MBRs), led AI Tea-Time sessions for 10–15 engineers, and collaborated cross-functionally with teams across AWS while supporting 15+ teams and 50+ services.Before that, I came up through Amazon\'s Technical Academy — a competitive internal program that trains non-SDE Amazonians into software development engineers through 10 months of intensive Java, AWS infrastructure, and distributed systems training.Outside of work, I\'m building three products- Afrolingo — an AI-powered African language learning platform- Geldzak — a financial wellness content engine- Tradr — an AI consensus trading systemI hold AWS Certified Solutions Architect and AWS Certified AI Practitioner certifications.Currently pursuing a BS in Computer Science (3.8 GPA) while deepening my focus on machine learning and quantitative methods through WorldQuant University\'s data science and deep learning programs.Open to SDE, ML Engineering, and AI Tooling roles.

Experience

1. Support Engineer

   Amazon Web Services (AWS)

   Dec 2024 — Present · Seattle, WA, US

   Served as Support Engineer on the Builder Tools team, personally supporting 2–3 teams and 7–8 services while resolving an average of tickets per month. Part of a team supporting 15+ teams and 50+ services across AWS- Pioneered adoption of Amazon Q and Kiro within the organization, creating agentic AI workflows that reduced time-to-resolution from hours to seconds for technical investigations, contributing to an org-wide initiative saving hours of manual effort annually- Built a customer issue analysis and categorization system used in Quarterly and Monthly Business Reviews (QBRs/MBRs), surfacing recurring pain points that drove measurable service improvements across 50+ supported services- Led \"AI Tea-Time\" knowledge-sharing sessions for 10–15 support engineers, training the team on emerging AI tools and driving toward the internal goal of 80% weekly AI tool adoption- Collaborated cross-functionally with teams across AWS (Cloud Desktop, SAS, Apollo) to diagnose and resolve complex infrastructure issues, improving response times for low to medium-severity customer cases- Developed internal tooling and automation scripts to streamline support workflows, reducing mean time to resolution (MTTR) and enabling 40–60% ticket deflection through AI-powered automation.

Education

• Florida State College at Jacksonville

  Associate of Science - AS, Information Technology

• National University

  Bachelor of Science - BS, Computer Science

• Year Up United

  Associate of Science - AS, Information Technology