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Vetted Site Reliability Engineering Professionals
Pre-screened and vetted.
Staff-level Software Engineer specializing in LLM inference infrastructure and scalable model serving
Staff Software Engineer specializing in distributed infrastructure and reliability
Russell Wong
Senior Software Engineer specializing in large-scale backend reliability and media platforms
“Backend/data engineer with experience on large-scale consumer platforms (Google and Meta), building high-traffic Python microservices (REST/gRPC) on Kubernetes with strong reliability/observability practices. Delivered AWS container-based deployments with CI/CD and IaC, and built AWS Glue ETL pipelines on S3 with schema evolution and data quality controls; also has demonstrated SQL tuning impact (15% latency reduction) and incident ownership for batch pipelines.”
Senior Software Engineer specializing in distributed systems, AI/ML, and healthcare platforms
Jacob Zimmerman
Director-level Engineering Platform leader specializing in cloud infrastructure, SRE, and SaaS compute
“Longtime early-stage startup operator (since 1998) now running a solo consulting practice focused on SaaS infrastructure and platform strategy. Former angel investor in a medical information SaaS company that went public, with a strong focus on making prototype/demo systems enterprise-ready through efficiency, reliability, and performance improvements, and a nuanced view of how AI/LLMs may change engineering team models.”
Hassaan Khan
Executive Technology Leader specializing in distributed systems, cloud infrastructure, and AI/ML
“Engineering leader/player-coach who built and validated a preference-based recommendation engine using clustering, including generating test data to evaluate how clusters evolve over time. Has SRE/DevOps experience and has owned production incidents end-to-end (logging-driven RCA and refactoring patterns that failed at large data scale). Emphasizes quality and platform stability via unit, integration, and load testing, and has managed performance via regular 1:1s and PIPs.”
Executive technology architect specializing in cloud platforms, SRE, and enterprise SaaS
Staff Software Engineer specializing in FinTech and distributed systems
Senior Software Engineer specializing in backend, distributed systems, and cloud platforms
Senior Full-Stack Engineer specializing in AI platforms, real-time collaboration, and observability
Executive Engineering Leader specializing in large-scale cloud infrastructure and distributed databases
Senior Software Engineer specializing in AI platforms, payments, and consumer systems
Principal Data Scientist & AI/ML Engineer specializing in LLMs, recommender systems, and MLOps
Staff AI Systems Engineer specializing in LLM platforms and distributed systems
Entry-Level Software Engineer specializing in AI developer platforms
Senior Software Engineer specializing in Java backend and OLAP systems for Ads platforms
Senior AI/ML Engineer specializing in LLM applications, RAG systems, and MLOps
Senior Software Engineer specializing in DevOps and CI/CD infrastructure reliability
Daozheng Chen
Staff Full-Stack AI Engineer specializing in FinTech and Enterprise SaaS
“Full-stack engineer with Yahoo Finance experience building AI-powered investment and analytics features. They combine modern TypeScript/React/NestJS development with strong backend systems skills in PostgreSQL, Redis, Kafka, and Kubernetes, and have driven architectural improvements from synchronous workflows to event-driven microservices in a high-traffic financial environment.”
Andrew Coven
Executive Software Engineering Leader specializing in AI/ML products and large-scale platforms
“Engineering leader who drove Lightroom Mobile’s roadmap at Adobe by enforcing reuse of Photoshop imaging tech to deliver RAW, non-destructive mobile editing with full Creative Cloud compatibility. In startup environments, has repeatedly scaled and professionalized engineering orgs (career ladders, evaluation systems, delivery process) and led high-stakes cloud/platform transformations—migrating off Heroku and consolidating fragmented AWS/GCP usage into a single GCP platform—improving reliability, deploy speed, and cutting cloud costs by 20%+.”