Vetted Code Review Professionals

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.”

“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.”

“Product engineer/designer with founder mindset who shipped a blockchain-enabled investor group/governance platform using Next.js (App Router), TypeScript, Prisma/Postgres, and Temporal. Emphasizes auth-centric onboarding (SSO + embedded wallet) to make dApp UX feel more like SaaS, and brings strong reliability practices (idempotent retries, reconciliation) plus experience demoing to investors and operating in seed-stage teams (ex-Vouched).”

“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.”

“Senior Unity developer who built a v2 narrative fiction engine end-to-end, including a portable TypeScript/JavaScript inkjs processing core and a Unity UI package that creators found significantly easier to use than the prior version. Has shipped cross-platform VR (Meta Quest) and mobile titles, implemented Unity Netcode multiplayer with host-authoritative flow, and integrated LLM-driven gameplay with automated agent-based testing and regression coverage.”

“Backend/data engineer who reports building production Python services (FastAPI + JWT) backed by Postgres and Redis, and modernizing data workflows using AWS Glue + PySpark with S3/RDS. States experience delivering AWS solutions (S3, SES, Cognito) and using golden datasets/snapshot testing for migration parity, with many details withheld due to NDAs. Seeking fully remote work with a $300k base salary expectation.”

“Frontend-focused engineer who led a full-scale CMS/dashboard build using React (with TypeScript), plus Node.js microservice APIs on AWS Lambda and MySQL. Emphasizes scalable component architecture, feature-based code organization, performance profiling via Chrome DevTools, and disciplined release practices (CI/CD, UAT gating, production monitoring) in fast-paced delivery cycles.”

“Frontend engineer with co-op experience at Nokia and prior work at Nimble, delivering React/TypeScript single-page onboarding flows and internal web apps. Builds from Figma to production React, emphasizes modular architecture and consistent UI via Material UI, and applies Jest-based unit/integration testing plus lazy loading to improve reliability and performance in both new and existing codebases.”

“Full-stack engineer from seed-stage Violet Labs who owned an end-to-end production "compare push results" feature for external integrations, including solving tricky false-positive success cases by validating against internal entity hashes and confirmed integration events. Experienced building React/TypeScript SPAs with a Node + Postgres backend, deploying via AWS/Kubernetes, and setting up CloudWatch logging/metrics/alarms with SNS paging.”

“Built an LLM-powered agent within the Nora AI analytics platform to automate e-commerce product performance analysis and generate actionable recommendations (pricing/inventory), designed with production-grade reliability patterns and observability. Emphasizes predictable, schema-validated tool/function-calling pipelines with robust fallbacks, idempotency, and guardrails for messy operational data.”

“Built and shipped a production LLM-powered email automation agent for procurement that ingests emails/attachments, classifies requests via rules+embeddings+LLM fallback, enriches responses with SAP inventory data, and generates templated replies. Architected it as an event-driven, idempotent Azure Functions/Queues pipeline with schema-constrained outputs, confidence gating, retries/circuit breakers, and Application Insights monitoring—cutting turnaround time from 4–7 days to near real-time while maintaining zero downtime.”

“ML/AI engineer with hands-on ownership of fraud detection and investigator-assist systems, combining anomaly detection with RAG-based LLM summarization in production. Stands out for translating research ideas into reliable cloud-deployed workflows that improved precision to 92%, cut review time by 25-30%, and increased investigator throughput by roughly 30% while also building reusable Python infrastructure for team-wide velocity.”

“Engineer at Syniti who uses AI tools pragmatically to speed development while maintaining quality through rigorous validation, code reviews, and CI/CD. Most notably, they leveraged AI-assisted testing to increase test coverage from 10% to 70%, and they are actively exploring more advanced agent-based development workflows.”

“Engineer with a mature, agent-oriented approach to AI-driven software development, using structured planning, TDD, and verification loops rather than ad hoc prompting. Has hands-on experience acting as a tech lead for multiple AI agents in an LLM intelligent routing project, coordinating implementation, testing, debugging, and edge-case review with strong attention to system tradeoffs.”

“Data engineering/software development candidate who built a stock market pipeline and uses that project to demonstrate strong architectural thinking across Kafka, Spark, and Airflow. They stand out for a pragmatic approach to AI: using tools like Copilot, ChatGPT, LangChain, and AutoGen to accelerate development while maintaining human oversight, testing, and system-level decision making.”

“Accenture engineer who built real-time smart mobility products (Verra Mobility) used by both consumers and government agencies, spanning React/TypeScript frontends and Node.js/GraphQL microservices with Kafka. Demonstrated strong delivery and reliability practices (CI/CD, feature flags, automated testing, CloudWatch observability) and achieved a ~20% GraphQL performance improvement supporting 50,000+ daily transactions, plus built an internal ops/support dashboard adopted into daily workflows.”

“Backend engineer who has shipped both high-throughput real-time systems and production LLM/RAG features. Built a database-free, local-first messaging service (Node/Express/Socket.IO) achieving ~1,500 msgs/sec at <25ms p95, and implemented a Go-based RAG recommendation pipeline with strict JSON/schema validation, catalog grounding, fallbacks, and eval loops that cut hallucinations to ~1–2% while reducing LLM costs ~60%.”

Ron Lei

Screened

Junior QA Automation Engineer specializing in Playwright E2E and API testing

San Francisco, CA3y exp

“QA automation-focused engineer who hardens production CI/CD by integrating and stabilizing end-to-end automated tests (tackling async UI flakiness, resilient assertions/selectors, and controlled test data). Demonstrates strong cross-layer troubleshooting by correlating logs and system metrics to resolve intermittent service reachability, then adding monitoring/alerts and documentation. Also partners directly with operators to improve real-world workflows by enhancing validation logic and error messaging.”

Femi Ayoade

Screened

Mid-level Robotics Controls Engineer specializing in ROS2 real-time motion control

Tustin, CA5y exp

“Robotics software engineer at Earthwise building a full ROS2 Humble warehouse AMR stack for bin picking—owning perception (Livox/Orbbec/RPLidar fusion + calibration), Nav2 navigation with custom planners/behavior trees, and application-layer nodes (barcode scanning, safety monitoring, web HMI). Demonstrated strong real-world debugging and performance tuning (sub-cm AprilTag docking; ~80% reduction in localization failures) plus solid simulation/CI practices (Gazebo + Docker + GitHub Actions).”

Uday Dorawala

Screened

Director-level Engineering Leader specializing in SaaS platforms, data, and cloud modernization

Raleigh, NC25y exp

“Former founder with an acquired venture who later led R&D at McClatchy and joined multiple startups. Identified a major client need and built a mobile app platform using ML and AR for home builders, driving adoption by dozens of customers and $1M+ ARR. Strong hands-on builder who can architect MVPs, iterate quickly with A/B testing and user feedback, and scale early engineering teams and culture.”

EMMANUEL ETIENNE

Screened

Engineering Manager specializing in FinTech money movement and AI-driven infrastructure

Brooklyn, NY12y exp

“Player-coach fintech engineer/engineering lead who built a deterministic payer-ID wire reconciliation system with Citi, including idempotent ingestion and webhook processing across Ruby and Go, materially reducing accounting manual work. Experienced in incident response (Plaid-related customer-impacting issue), stakeholder-driven MVP scoping for ACH status visibility, and delivery acceleration via infrastructure templating (EC2) and standardized Magento project setups.”

Shravani Koona

Screened

Junior Full-Stack Software Engineer specializing in cloud-native microservices

United States3y exp

“Backend/data engineer with experience at Assurant and Capgemini, focused on reliability and performance at scale. Improved high-latency backend APIs by adding and iterating on a Redis caching layer driven by CloudWatch/monitoring metrics, and built scalable BI pipelines that normalize messy multi-source enterprise data with strong observability and error handling. Familiar with LLM/RAG architecture and practical guardrails, though has not yet shipped an LLM feature to production.”