Vetted Pinecone Professionals

“Engineer with a notably mature AI-native development process: uses Claude/Claude Code in a test-first, iterative workflow and has led multi-agent builds across frontend, backend, and testing. Most notably, they led development of an AI voice agent platform, creating custom agent skills and enforcing clear architectural boundaries to deliver a stable, scalable system.”

“Backend/platform engineer with significant ownership at GoDaddy, where they built a real-time personalization and decisioning system that drove about $7M in annualized revenue and serves roughly 4M requests per day. Also operates as a solo engineer for a global human-rights legal-tech nonprofit, building the full platform and graph-based matching engine for 700+ partner organizations. Brings a strong blend of production backend rigor, platform thinking, and practical AI orchestration.”

“ML/GenAI engineer with strong end-to-end production ownership across predictive ML, RAG systems, and LLM routing. They pair solid platform engineering skills with measurable business impact, including 15% churn reduction, 35% support ticket deflection, 45% GenAI cost savings, and a shared inference library that cut deployment time from weeks to days.”

“ML/AI engineer with hands-on ownership of production document intelligence and GenAI systems, spanning model experimentation, AWS deployment, monitoring, and iterative optimization. Stands out for turning document-heavy workflows into reliable, near real-time products with measurable gains in accuracy, latency, and manual-effort reduction, while also shipping citation-grounded RAG features that drove user trust and adoption.”

Harsh Sanas

Screened

Junior Full-Stack Engineer specializing in AI systems and cloud applications

San Francisco, CA2y exp

“Full-stack engineer with a strong applied AI bent who has built both a real-time EV charging platform and a production text-to-SQL system. Particularly compelling for teams needing someone who can bridge frontend, backend, infrastructure, and LLM evaluation/safety work, with experience shipping under early-stage ambiguity and integrating software with real-world hardware.”

“Backend engineer who built and iterated a secure, multi-tenant RAG system over a large document corpus, emphasizing strict RBAC/ACL isolation, hybrid retrieval (vector+keyword), reranking, and strong observability to balance relevance, latency, and cost. Also led production refactors/migrations using strangler + feature flags/dual writes and has experience catching subtle real-world failure modes (including in a sensor calibration optimization pipeline).”

“AI/ML engineer who has shipped both a safety-critical mental health RAG chatbot (Mistral 7B + Pinecone) with automated faithfulness/toxicity monitoring and a deep Q-learning investment recommendation engine at Lincoln Financial Group. Strong in production MLOps and orchestration (AWS Lambda/CloudWatch/SageMaker, Docker, AKS) and in translating regulated-domain requirements (clinical reliability, fiduciary duty) into measurable model constraints and monitoring.”

“Senior full-stack engineer with seed-stage fintech experience who has led payment API development, implemented compliance-related standards, and built production systems across React, Go, Python, Node.js, and PostgreSQL. Notable impact includes enabling a first major client launch, reducing logistics response times by 30%, improving page load times by 40%+, and cutting analytics report generation from minutes to seconds.”

“Full-stack engineer with strong AI systems and B2B SaaS experience across BrightOps, Zapier, Nordstrom, and Calendly. They’ve owned architecture for an AI-powered tutoring platform, improved retrieval quality with a hybrid vector-plus-keyword approach, and built Go services processing over 1 million student events per day. Particularly compelling for teams building data-intensive, reliability-critical products with LLM, workflow automation, or compliance-oriented use cases.”