Hi, I'm Natalie Kadonaga - Software Engineer, Cloud AI at Google
I am driven by the complexity of cloud AI and the challenge of building systems that scale globally. I thrive in environments where technical curiosity is encouraged and where I can tackle ambiguous problems.
At a glance
Curated signals on strengths, focus areas, and how they can help.
Developed strong technical foundations through high-impact internships at Google and academic roles at Harvey Mudd College.
Currently specializes in designing and maintaining scalable cloud AI systems for global infrastructure platforms.
Provides expertise in distributed systems architecture and offers guidance on early-career engineering transitions.
🚀 Career trajectory
Foundational Development
Established technical mastery during rigorous computer science studies and early internships.
✦ Academic Excellence
✦ Technical Foundations
Specialized Cloud Engineering
Transitioned to full-time focus on cloud AI systems within global technology infrastructure.
✦ Cloud Computing
✦ AI Infrastructure
💪🏻 Superpowers
Scalable Cloud Architecture
Engineering resilient systems for global scale
✦ Architecting distributed systems for cloud-based AI environments
✦ Optimizing data pipelines for high-velocity model deployment
Academic Technical Foundation
Merging theoretical rigor with engineering discipline
✦ Bridging complex computer science concepts into practical solutions
✦ Mentoring peers through foundational programming and algorithmic logic
Collaborative Problem Solving
Navigating cross-functional team dynamics
✦ Translating ambiguous requirements into executable technical roadmaps
✦ Fostering knowledge sharing across multidisciplinary engineering cohorts
I'm excited about
✦ Exploring advancements in generative AI and cloud infrastructure.
✦ Engaging with communities centered on emerging software development methodologies.
✦ Finding opportunities to apply technical expertise toward innovative startup ecosystems.
I can help with
✦ Providing technical guidance on cloud system architecture for early-stage teams.
✦ Offering advice on navigating the transition from computer science student to engineer.
✦ Supporting peer reviews for complex algorithmic problems and distributed system design.
I would love your help on
✦ Connecting with mentors who have navigated the path from individual contributor to leadership.
✦ Learning about the latest trends in scalable AI infrastructure and performance optimization.
✦ Finding new opportunities to participate in deep-tech research and development circles.