Vetted Full-Stack Development Professionals

Vatsal Gabani

Screened ReferencesStrong rec.

Mid Software Engineer specializing in backend systems and AI-enabled platforms

California, USA4y exp

“Full-stack engineer with hands-on ownership of a support ticket intelligence platform, spanning React/TypeScript frontend work and backend API, PostgreSQL, Redis, and Docker-based deployment. They stand out for driving practical architecture and performance improvements in production, including moving heavy processing async and cutting response times from about 300ms to 150ms while improving reliability.”

“Senior engineering leader with experience across cybersecurity, retail commerce, consulting, and media platforms, combining large-scale org leadership with hands-on architecture depth. Notable for driving measurable cloud modernization outcomes—multi-million-dollar cost savings, major latency and MTTR reductions, and compliance-heavy transformations—while also leading AI/NLP and consumer product simplification initiatives.”

Cheyenne Vasseli

Screened ReferencesStrong rec.

Senior DevOps Architect specializing in cloud and platform engineering

8y exp

“Senior DevOps/infrastructure leader currently owning all DevOps for Audi Digital, including audiusa.com and its supporting cloud, CDN, CI/CD, and repository ecosystem. Stands out for delivering two simultaneous enterprise-scale migrations—100+ repo GitHub migration and Apollo Router supergraph platform migration—two months early with minimal disruption, while operating deeply hands-on in Kubernetes, containers, and cloud architecture.”

David Proctor

Screened ReferencesStrong rec.

Executive Enterprise Architecture & AI Strategy Leader specializing in modernization and agentic AI platforms

Colorado Springs, CO25y exp

“Technically and operationally oriented builder with startup ideas of their own, including an AI services firm in the ideation stage. Stands out for a practical understanding of venture studios and accelerators, with fluency in founder-market fit, MVP validation, hiring, and investor readiness, and a measured approach to going all-in only on high-signal opportunities.”

“Founder/idea lead behind InvantX, an AI-powered product helping people make better decisions with their own data. Developed the business model canvas and MVP plan, set up an early customer feedback loop, and iterates roadmap/architecture based on beta-user learning. Has participated in accelerators including FinAccelerate, Pegasus, and an NVIDIA program (AWS credits), and applies a metrics-driven, structured approach to traction building.”

Ashi Sinha

Screened

Junior Software Engineer specializing in full-stack and ML/NLP systems

New York City, NY2y exp

“Entry-level full-stack engineer with internship experience at Amazon (Appstore IAP flow + uninstall recommendation workflow) and a health-tech startup (OneVector) where they built a DSUR reporting workflow end-to-end, including document generation, S3-backed versioning/metadata, and secure preview/download. Demonstrates strong production debugging and reliability mindset (instrumentation, deterministic retrieval, idempotent writes) and focuses on UX/performance in high-stakes user flows.”

“Seasoned operator with 20+ years across corporate and startup environments, currently serving as CEO of an AI-powered augmented reality company building a 3D heads-up display for cars. Has raised about $3M pre-Series A and is also advising another AR company on automotive commercialization and Series B fundraising, with a strong VC network in deep tech, mobility, and transportation.”

Zahaan Khan

Screened

Mid-Level Full-Stack Software Engineer specializing in ads transparency platforms

San Jose, USA6y exp

“TikTok engineer (4 years) who built and owned multiple ad transparency platforms used by internal teams and advertisers worldwide. Strong full-stack profile spanning Next.js/TypeScript + Redux frontends, a secure/optimized BFF layer, and event-driven backend workflows (Kafka, retries/DLQ, Redis idempotency) with heavy emphasis on observability and performance; cites a 20% moderation efficiency gain on a modernized legacy tool.”

Patrick Jose

Screened

Senior AI Engineer specializing in LLM applications and full-stack systems

San Francisco, CA8y exp

“Built and owned a production LLM/RAG customer support assistant end-to-end, from prototype through deployment, monitoring, and iteration. Their work automated roughly 40% of common support queries and cut response times by about 30%, while also creating reusable Python inference services that improved consistency and team velocity.”