Hi, I'm Roozbeh Nia - Software Engineer at Clifton AI
I am driven by the complexity of distributed systems and the potential of AI. I thrive where deep academic research meets high-scale production, solving architectural challenges alongside ambitious, innovative teams.
At a glance
Curated signals on strengths, focus areas, and how they can help.
Holds a PhD from UC Davis with a proven history of high-scale engineering at major tech firms.
Currently specializes in data and distributed infrastructure within the evolving artificial intelligence landscape.
Provides expert guidance on scaling software architectures and navigating technical engineering management.
🚀 Career trajectory
Foundational Research
Completed PhD at UC Davis, building a deep analytical and technical problem-solving methodology.
✦ PhD
✦ Researcher
Big Tech Scaling
Transitioned into large-scale distributed systems and engineering leadership at top-tier tech firms.
✦ Infrastructure
✦ Leadership
AI Infrastructure Shift
Focused on specialized roles within the artificial intelligence ecosystem, bridging systems and intelligence.
✦ AI
✦ Systems
💪🏻 Superpowers
Systems Architecture Architect
Engineering robust, high-throughput distributed infrastructure at scale.
✦ Architected reliable data systems supporting millions of concurrent users.
✦ Optimized backend performance and infrastructure efficiency during rapid scaling phases.
Technical Leadership Mentor
Guiding high-performing engineering teams through complex product cycles.
✦ Led cross-functional engineering teams to deliver mission-critical software initiatives.
✦ Cultivated engineering excellence through mentorship and strategic team alignment.
Strategic Research Integration
Bridging academic rigor with practical machine learning applications.
✦ Utilized advanced academic research to drive innovation in data-driven products.
✦ Bridged the gap between theoretical models and performant production deployment.
I'm excited about
✦ Exploring the latest advancements in distributed systems for modern AI applications.
✦ Engaging with a network of technical founders to discuss infrastructure architecture.
✦ Finding new ways to apply complex data engineering to emerging startup problems.
I can help with
✦ Providing technical deep dives into distributed system scalability and architecture.
✦ Mentoring early-stage engineering teams on management and technical career growth.
✦ Advising on the transition from academic research to production-level engineering.
I would love your help on
✦ Connecting with peers navigating the current shift toward AI-integrated software development.
✦ Gaining insights into the latest community-driven standards for distributed data infrastructure.
✦ Finding opportunities to participate in peer groups focused on long-term systems thinking.