Vetted Software Developers in the Bay Area

“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.”

Sean Brennan

Screened

Senior Software Engineer specializing in backend platforms and cloud systems

Oakland, CA28y exp

“Engineer with a track record of taking on messy, high-ambiguity systems that others avoid, including a Python rewrite of Google Search Appliance's settings migrator that achieved 95% test coverage and zero bugs. Has also built internal full-stack planning tools at Capital One using React, Kotlin, and Airflow/DBT data pipelines, and brings specialized insurance analytics experience from catastrophe risk modeling for insurers.”

“Operator-turned-aspiring founder with experience building CI, cloud, and AI businesses at Harness, including P&L ownership and 0-to-1 execution. Exploring an AI-native infrastructure/control-plane thesis focused on moving enterprise workflows from AI assistance to execution, with a strong emphasis on ROI, coordination gaps, and durable moats.”

Vernon Quan

Screened

Senior Full-Stack Software Engineer specializing in TypeScript, React, and Node.js

Menlo Park, CA7y exp

“Meta engineer who owned a heavily used internal goals/performance management feature end-to-end, driving major responsiveness improvements by restructuring frontend data loading and adding backend caching (Memcached), cache warmups, and query/index tuning. Strong focus on production quality: observability, error monitoring, and improving test coverage to prevent regressions during peak review cycles.”

Sanket Patel

Screened

Director-level Front-End Engineering Leader specializing in scalable web and mobile apps

Palo Alto, CA17y exp

“Amazon engineer/leader who drove a major modernization of the AWS Database Migration Service Console, migrating a monolithic UI to a micro-frontend architecture while improving performance, reliability, and engineering standards. Operates as a player-coach (80/20 hands-on/management), with demonstrated incident ownership and process improvements across Amazon and Walmart Labs.”

“Customer-facing technical professional with Amazon incident-management experience who helps drive adoption of complex ML/LLM solutions by delivering hands-on demos and rapid model fine-tuning. Applies a disciplined debugging approach (repro + logs/metrics + severity triage) and maintains runbooks to resolve SEV2 issues in ~1 hour, while also partnering with sales/customer teams to ship patches and new features based on feedback.”

Brian Paul

Screened

Junior Frontend Software Engineer specializing in FinTech and crypto products

San Francisco, CA2y exp

“Frontend engineer with Coinbase experience building high-trust crypto product flows such as staking and asset wrapping, plus data-heavy verified pool visualizations. Stands out for scalable React/TypeScript architecture, clean data-transformation layers, and strong attention to maintainability, performance, and design-system consistency.”

Ashraf Jahangeer

Screened

Executive engineering leader specializing in AI, SaaS, and large-scale platform transformation

Pleasanton, CA19y exp

“Senior engineering executive with 20+ years of experience scaling and restructuring product engineering organizations across startups and larger companies. Over the last 8 years, they grew teams significantly at Stitch Fix and EasyPost, led monolith-to-microservices modernization, and launched products associated with 50M-100M+ ARR. Currently a hands-on VP Engineering at BlueCargo, combining executive leadership with direct technical contribution when customer-critical issues arise.”

“ML/AI engineer with experience at Uber and Scale AI, focused on customer service automation across both classical NLP and generative AI systems. Has owned systems from experimentation through production on AWS, including LLM fine-tuning, RAG optimization, safety evaluation, and internal Python platform tooling that improved consistency and engineering velocity.”

“Seed-stage startup engineer owning features end-to-end across full-stack development, DevOps, rollout, and post-launch maintenance. Built data ingestion and evaluation workflows for an LLM data-quality platform using Next.js, MongoDB, Postgres, and GCP Pub/Sub, with a strong focus on reliability, caching, and pragmatic performance improvements.”