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Vetted Full Stack Software Engineers in the Bay Area
Pre-screened and vetted in the Bay Area.
Mid-Level Full-Stack Engineer specializing in data-intensive SaaS products
Mid-level Full-Stack Software Engineer specializing in FinTech and Healthcare
Intern Machine Learning Engineer specializing in LLM agents and full-stack systems
Mid-level Full-Stack Engineer specializing in .NET, Python, and cloud platforms
Junior Full-Stack Software Engineer specializing in cloud-native web apps and CI/CD automation
Mid-level Full-Stack Software Engineer specializing in scalable SaaS and developer platforms
Mid-level Full-Stack Software Engineer specializing in AI agents and distributed systems
Junior Full-Stack Software Engineer specializing in geospatial and real-time data systems
Senior Full-Stack Software Engineer specializing in Healthcare IT and FinTech integrations
Mid-level Full-Stack Software Engineer specializing in cloud, data visualization, and healthcare AI
Junior Full-Stack Software Engineer specializing in FinTech APIs
Mid-Level Full-Stack Software Engineer specializing in cloud-native distributed systems and AI
Mid-level Full-Stack Engineer specializing in backend systems and FinTech
Mid-level Full-Stack Software Engineer specializing in React and Python APIs
Junior Full-Stack Software Engineer specializing in defense and cloud web applications
Kevin Mathews
Mid-Level Full-Stack Software Engineer specializing in Next.js, React, and cloud platforms
“Full-stack engineer from Vagaro who owned an end-to-end rebuild of a sluggish WordPress sales site into a Next.js 15 app hosted on Azure, adding Hygraph headless CMS, SSR, i18n, and a reusable component library. Instrumented Amplitude + A/B testing/heatmaps and reports a 10% sales lift post-launch; also has AWS ops experience (S3/IAM/CloudWatch) and has built ingestion pipelines including LLM-powered unstructured data processing with dead-letter handling.”
Ranxin Li
Mid-Level AI/Full-Stack Engineer specializing in agentic LLM systems and RAG
“Built and deployed Clyra.AI, an AI-driven daily scheduling product that uses a LangGraph-based multi-agent LLM pipeline (task extraction, verification, reflection) grounded with strict RAG over emails/documents/calendars and real-world signals like health metrics. Designed a custom agent orchestrator with bounded loops/termination conditions and a self-auditing verification/reflection layer to reduce hallucinations while controlling latency and cost via caching and model distillation.”