Vetted Bash Professionals

Peter Gluck

Screened ReferencesStrong rec.

Principal Software Engineer specializing in scalable, secure multi-platform systems

La Crescenta, CA14y exp

“Engineering leader and former CTO/Disney|ABC engineering manager who built white-label mobile app architecture that supported a branded app and successful exit, and later scaled Disney Channel brand app teams across iOS/Android/web and major OTT platforms. Led kid-safety architecture for DisneyNOW (“Junior mode” with PIN) and partnered with product/legal on COPPA compliance, emphasizing maintainable tech choices and strong execution processes.”

“Senior infrastructure/platform engineer with deep IBM Power/AIX (Power9, VIOS, HMC, LPAR/DLPAR) and PowerHA production ownership at scale (40 frames / ~300 LPARs), including hands-on outage recovery and performance tuning. Also delivers modern DevOps/IaC capabilities—CI/CD for Kubernetes microservices and Terraform-based multi-account AWS (EKS/VPC/IAM/RDS) with drift detection and safe rollout controls.”

Bocheng Wan

Screened

Mid-level Software Engineer specializing in consumer robotics and machine learning

Sunnyvale, CA4y exp

“Developer with a structured AI-assisted coding workflow centered on algorithmic rigor, type-safe scaffolding, and spec-driven modular design. Used Claude Code to help build an Android SDK for IPC, quickly ramping up on AIDL and compressing delivery including unit tests from several weeks to two weeks.”

“Robotics student who built a fully autonomous "Pacman" robot car using ROS 2, integrating LiDAR/IMU sensing with localization, autonomous driving, and a custom RRT + A* planner. Demonstrated practical embedded optimization on an RP2040 by balancing replanning frequency with safety via rapid collision checks.”

“Game UI engineer with shipped experience on Paladins (Unreal Engine 3/C++), including an in-game store with automated grid-based recommendation layout and an inventory UI built for PC/PlayStation/Xbox/Switch. Emphasizes production readiness through clean separation of UI/data, strong documentation for engineering and content workflows, and memory-conscious UI patterns (pooled entries/paged navigation) for constrained platforms like Switch.”

Vinay Ramrupe

Screened

Mid AI/ML Engineer specializing in LLM and enterprise generative AI

San Francisco, CA5y exp

“ML/AI engineer focused on taking LLM systems from experimentation to reliable production, including enterprise copilot and RAG-based knowledge retrieval use cases. Stands out for combining data pipelines, model training, inference optimization, automated evaluation, and safety guardrails, with cited impact including 20% throughput gains and 30% less manual evaluation effort.”