Vetted Code Reviews Professionals

“AI engineer with experience taking a GPT-4-powered GenAI career coach toward production on Azure AI Foundry, re-architecting the backend with hybrid (vector + keyword) search and RAG optimizations to cut latency by 50%. Also has client-facing TCS experience building healthcare ETL pipelines and delivering error-free monthly reports, plus current work analyzing agentic system reasoning traces and guardrail drift as an AI research fellow.”

“Founding AI engineer at an AI SaaS startup who built the full GTM knowledge and retrieval stack for non-technical teams, driving 60% less manual effort and 25% faster deployments. Also brings enterprise B2B SaaS integration experience from Wipro, including external API/documentation work for large-scale partner ecosystems.”

“Full-stack engineer who built and scaled an AI-powered web product (React/Next.js + TypeScript/NestJS) with MongoDB, Redis, and RabbitMQ. Strong in rapid iteration while maintaining production quality—uses versioned APIs, feature flags, CI/CD, and observability (correlation IDs/structured logs) to ship frequently and debug distributed workflows. Also created an internal operations dashboard for real-time visibility and control of background jobs/AI workflows that was adopted quickly by ops and product teams.”

Nicholas Pinero

Screened ReferencesStrong rec.

Mid-level Software Engineer specializing in Unity XR/VR training simulations

Remote, USA8y exp

“Unity/C# VR developer who owned a next-gen replay/review system end-to-end, improving determinism so recorded actions (e.g., shots) replayed consistently. Also built a Jenkins-triggered GameDriver-based VR QA automation suite that ran nightly builds and cut manual QA effort by ~75%, and contributed to Photon PUN multiuser mode with hands-on network debugging.”

“Unity/C# AR developer who built a Pokemon Go-like location-based gameplay system end-to-end, spanning backend geospatial filtering (bounding box + Haversine), native iOS location/heading plugins, and Unity AR/UI/spawn logic, with a strong focus on real-world reliability issues like GPS drift. Also prototyped an AI pipeline combining on-device Core ML image segmentation with cloud-hosted PiFU HD (Docker/Kubernetes on GCP with GPU provisioning), ultimately shelving it due to cost/latency and model reliability constraints.”

Preethi Bandari

Screened ReferencesStrong rec.

Mid-level Full-Stack Developer specializing in scalable web applications

Memphis, TN5y exp

“Developer who uses AI tools pragmatically to accelerate coding while keeping full ownership of system design and decision-making. Emphasizes rigorous review, testing, and alignment with architecture, security, and performance standards, and stays current on AI through both industry sources and hands-on experimentation.”

“Built a production AI-native internal onboarding feature that reduced manual product setup effort by combining barcode API data, product photos, structured LLM outputs, and a polished real-time camera UI. Demonstrates hands-on experience across the full stack of LLM systems: prompt/schema design, multimodal inputs, backend orchestration with SQS and vector retrieval, and production reliability through evals, telemetry, and drift monitoring.”

Sophie Adams

Screened ReferencesStrong rec.

Senior Full-Stack Engineer specializing in event technology and interactive systems

New York, NY20y exp

“Full-stack product engineer in event tech who has owned AI-powered web products from architecture to live production, including a no-code SaaS/marketplace for event activations and real-time AI kiosk experiences. Particularly strong in building for non-technical users in high-stakes live environments, with hands-on experience across Vue/Laravel, LLM workflows, image generation pipelines, and operational reliability.”

Rathi Anand

Screened ReferencesStrong rec.

Senior Full-Stack Software Engineer specializing in Insurance, FinTech, and AI/ML applications

Dublin, CA17y exp

“AI/backend engineer who fine-tuned and deployed a production LLM chatbot using a LangChain + FAISS RAG pipeline, improving latency with PEFT/LoRA and driving strong business impact (40% customer adoption; 92% satisfaction). Also served as technical lead on a data aggregation system for underwriting/quoting, introducing GraphQL for more efficient, maintainable querying and applying CDC to keep cached ranking data fresh at scale.”

Ron Buchanan

Screened ReferencesStrong rec.

Executive technology leader specializing in cloud architecture and Healthcare IT

Summerville, SC20y exp

“Startup-focused builder currently developing a values-driven multi-platform mobile app in beta. Previously led a major technical turnaround at Lucina Analytics, taking the product from 0-to-1 and rebuilding it into an enterprise Azure-based SaaS platform that contributed to its acquisition by Unified Women's Health.”

“Frontend engineer/lead who has owned end-to-end architecture for large customer-facing React/Next.js platforms, emphasizing strong API contracts (GraphQL + TypeScript codegen), automated quality guardrails, and performance as a feature. Built complex workflow UIs including a multi-step patient booking flow for New York’s largest healthcare provider and an admin dashboard handling 400,000+ USDA ingredient records, with disciplined state management, staged rollouts, and real-user monitoring.”

“Backend/platform engineer in healthcare and consulting (Molina Healthcare, TCS) who productionized real-time eligibility/authorization and care navigation workflows with strong reliability and HIPAA security. Demonstrated measurable performance gains (≈40% latency reduction, ~99% uptime) using Spring Boot APIs, SQS decoupling, Redis caching, and deep observability, and regularly leads technical demos that accelerate client adoption.”

Viacheslav Bulba

Screened

Senior QA Automation Engineer specializing in UI/API test automation and CI/CD

Las Vegas, Nevada15y exp

“QA professional with 15+ years testing a variety of applications (not games), experienced partnering with developers/designers/product owners across the feature lifecycle. Brings a disciplined, methodology-driven approach to test design, regression coverage, and high-quality defect reporting using tools like Jira, TestRail, qTest, and HPQC; targeting ~100K base (flexible based on total package).”

“Frontend engineer experienced delivering React + TypeScript dashboards end-to-end, including real-time updates via WebSockets and scalable component architecture. Has improved inherited codebases by building shared component libraries and performance optimizations (lazy loading/memoization), reporting ~20% faster feature delivery, and ships major features with QA rigor and feature-flagged rollouts driven by analytics and user feedback.”