Vetted Unit Testing Professionals

Geetha Sri Kasu

Screened

Mid-level Software Engineer specializing in Java/Spring Boot, Kafka, and AWS

5y exp

“Software engineer who owned an end-to-end self-service reporting workflow (secure APIs, async/batched processing, and React UI), improving report generation performance by ~30–40% and reducing manual support effort. Also built a RAG/embeddings prototype over internal docs and service logs with grounding-focused guardrails, and has a strong reliability/observability mindset (retries, DLQs, CI/CD validation, dashboards/tracing) for distributed workflows.”

“Platform/infrastructure-focused engineer with hands-on experience automating AWS EKS upgrades in Python, building observability around logs/metrics/SLOs, and migrating Terraform delivery from CodePipeline to Atlantis. They describe shipping automation that handled 140 resources across 50+ Terraform files ahead of schedule and debugging a Karpenter/CoreDNS regression in Kubernetes by tracing it from regional traffic spikes to a missing local DNS cache configuration.”

Mustafa Ali

Screened

Mid-level Software Engineer specializing in backend systems and AI

Boston, MA4y exp

“Founding/early backend engineer at ATICA Global who built the company's core hotel property management platform from an empty repo into a production system used by 500+ hotel clients. Combines strong backend architecture with pragmatic product execution, including a dynamic pricing engine that increased partner revenue 17% YoY and an AI-powered sentiment pipeline processing 200K+ reviews/month.”

“Autonomous driving engineer from iFLYTEK who shipped 5+ middleware modules for vehicles across three models, with deep experience in reliability, IPC performance, and real-world system hardening. Stands out for translating flaky production behavior into measurable signals—resolving 30+ faults, cutting backlog 39%, improving latency 20%, and supporting 500+ hours of road testing with 99%+ reliability.”

“ML/AI engineer with strong end-to-end production ownership across predictive ML and Generative AI use cases. They built a churn prediction platform that cut churn 12% and preserved about $1.2M in annual revenue, and also shipped a RAG-based support assistant that reduced ticket resolution time 30% while improving agent satisfaction and onboarding speed.”

Yash Patel

Screened

Mid AI/ML Engineer specializing in MLOps and cloud platforms

Texas, USA3y exp

“ML/AI engineer with strong end-to-end production ownership across classical ML and GenAI systems. Built and deployed predictive analytics and RAG-based internal tools on AWS/Kubernetes with measurable impact on accuracy, latency, deployment speed, safety, and user productivity.”

“Engineering leader focused on multi-cloud platform modernization, combining deep hands-on expertise in Kubernetes, Terraform, GitOps, and DevSecOps with management of 18-person DevOps/SRE/software teams. Particularly strong in building secure, scalable enterprise SaaS infrastructure and Spark/Databricks data platforms while driving cross-functional standardization, reliability, and faster release cycles.”

“Shopify full-stack engineer focused on AI/LLM-powered merchant automation products. They have hands-on experience building React/TypeScript and Python/FastAPI systems for long-running agentic workflows, including orchestration, guardrails, observability, and customer-facing trust features, with measurable gains in task completion and latency.”

“Full-stack builder with hands-on experience spanning a MERN e-commerce product, an AI code review agent, and an ambiguous AWS internship project involving PyTorch/TensorFlow support in Redshift. Particularly interesting for recruiters because they combine product-minded engineering with AI agent reliability work, including CI/CD integration, telemetry via Weights & Biases, and measurable impact like 80% reduction in manual review effort.”

“Frontend engineer focused on React and TypeScript dashboards with dense data, fast search/filter workflows, and reusable UI architecture. They stand out for improving production performance by identifying unnecessary re-renders, optimizing state and data loading, and making complex reporting interfaces easier to navigate.”

Ryan Peterson

Screened

Senior Full-Stack Engineer specializing in Python web and AI applications

New York, USA8y exp

“Backend-heavy full-stack engineer with startup fintech experience who built a real-time lending eligibility service that cut decision time from 12-24 hours to under 5 seconds and lifted conversion by ~15%. Also has B2B SaaS experience automating construction workflows, with strong hands-on work across React/TypeScript, Python/FastAPI, Node.js, Kafka, Redis, and some Go.”

“ML/AI engineer with hands-on ownership of both classical ML and GenAI systems in production. They built an end-to-end churn prediction service on AWS and also shipped RAG-based document search/summarization features, with clear experience in monitoring, hallucination reduction, cost/latency optimization, and creating shared Python/LLM infrastructure used across teams.”