Akhass Wasti
Software Development Manager @Ring
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WORK HISTORY
Software Development Manager @Ring
London, GB
Defined a unified playback roadmap across transcoding, WebRTC streaming, and video event services; drove legacy service deprecation to $3.6M in annual savings- Lead 13 engineers across London and Cambridge, owning 7 microservices (6 production-critical) that process 3.3B+ daily requests for Ring\'s 70M+ devices worldwide- Scaled the team through 88 interviews and promoted 4 engineers to the next level; mentored 3 interns who all received return offers and joined full-time- Onboarded 100% of engineers onto AI coding tools (Claude Code, Cursor, Q CLI); drove a 3x increase in code and features shipped to production over 9 months- Owned operational excellence and incident response across all 7 services; managed 773+ severity-2 tickets with oncall rotation, runbooks, and review standards- Led cross-functional coordination across 4 concurrent service migration programs; aligned partner teams on shared timelines and quality standards
EDUCATION
University of Cambridge
MEng, BA & MA, Information and Computer Engineering
SKILLS
ABOUT AKHASS WASTI
I build AI-native engineering teams that operate at massive scale. As an engineering manager at Amazon Ring, I lead 13 engineers across London and Cambridge, owning 7 mission critical cloud services that process 5B+ daily requests at availability for 70M+ devices worldwide, from real-time video streaming and on-demand low-latency transcoding to time-lapse generation and secure media delivery.I joined Amazon as an SDE I out of Cambridge and progressed to SDM in 4.5 years, spending just 10 months at Senior SDE before stepping into management. That velocity came from staying close to the systems I build. I still lead architecture decisions, contribute code (through agents running in the background!), and drive the reliability and security culture that keeps production-critical services running at global scale.What excites me most right now is how AI is changing the way engineering teams work. After onboarding 100% of my engineers onto AI coding tools, we measured a 3x increase in shipped code and features over nine months. I don\'t just want to adopt AI tooling; I want to prove it works at scale, build the workflows around it, and help teams get there.Before Amazon, I studied Information and Computer Engineering at Trinity College Cambridge (specializing in machine learning and computer vision) and built a chatbot generation platform at IBM that became a US patent with 49 forward citations. I hold 4 granted US patents spanning conversational AI, intelligent interfaces, and IoT video infrastructure, with a fifth pending.Real-time media processing at billions of daily requests shares deep technical DNA with AI inference pipelines: high-throughput, latency-sensitive, event-driven architectures at massive scale. I enjoy working in engineering leadership roles at AI-focused companies where infrastructure discipline, people investment, and AI-native thinking come together.
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