Vetted Selenium Professionals

Vigynesh Bhatt

Screened ReferencesStrong rec.

Mid-level Software Engineer specializing in backend, cloud, and ML systems

Salt Lake City, UT4y exp

“Software engineer with experience across Goldman Sachs, BYU Broadcasting, Juniper Networks, and an edtech startup (Doubtnut), spanning data migrations, AWS-based media backends, and microservices observability. Built a Redis/ElastiCache caching layer in front of DynamoDB/S3 to improve media delivery latency and cost, and created an SEO indexing automation tool using the Google Search Console API that saved ~15–30 person-hours per day.”

“Player-coach engineering leader focused on AWS ML infrastructure and deep learning image delivery: provisioned EKS/Kubernetes for multi-node training and automated image release pipelines (Python + AWS CDK) to cut release time from 2 weeks to 1. Also built customer migration tooling for SageMaker HyperPod and owned a security incident end-to-end, implementing prevention tests and process improvements.”

Yernar Smagulov

Screened

Mid-level Software Engineer specializing in autonomous vehicle operations and test automation

Foster City, CA4y exp

“Hands-on Python/IoT engineer with experience spanning research labs and autonomous vehicles (Zoox), focused on making data/decision-support systems reliable in production. Has deployed and Dockerized Python tools with pinned dependencies, built sensor-based on-prem data collection systems (aquafeed evaluation), and troubleshot telemetry issues down to a failing switch port using logs, multimeter checks, and network diagnostics.”

Kaushik Sriram

Screened

Mid-level Software Engineer specializing in event-driven FinTech backend systems

San Francisco, CA5y exp

“Senior/Staff-level backend/platform engineer who owned Stripe’s global payout settlement system end-to-end, building an event-driven Python/Kafka platform processing millions of events daily across 30+ countries. Deep experience operating high-reliability distributed systems in production (incidents, replays/backfills, schema evolution, observability) and scaling on AWS/EKS with strong testing and deployment practices.”

“Built and operationalized an internal LLM/RAG system for engineering specs—starting with an at-home prototype using real ERP documents, then securing hardware, standing up a GPU/software stack, and deploying through UAT to production. Identified organizational gaps (no shared spec repository) and created a queryable RAG database that reportedly cut document discovery from days/weeks to minutes, while also resolving retrieval issues via improved PDF-aware chunking.”

Timothy Lee

Screened

Senior Full-Stack Engineer specializing in AI platforms and scalable web systems

Live Oak, FL11y exp

“Built and shipped production agentic/LLM systems that could safely perform real customer and subscription operations, not just answer questions. Demonstrates unusually strong depth in agent orchestration, tool safety, evals, tracing, and backend workflow design across Node.js/TypeScript, Go, Redis, Postgres, Kafka, and GPT-4.”

“Built and shipped production AI systems spanning customer support automation at Uber, privacy-preserving federated health modeling on iOS, and an open-source semantic search layer for Postgres. Stands out for combining strong LLM/product instincts with rigorous eval design, measurable production impact, and zero-to-one execution across backend, mobile, and developer infrastructure.”