Vetted AWS Professionals

“Frontend-focused engineer who has delivered an end-to-end React SPA with a .NET 9 backend on Azure, deploying via Azure Container Apps and leveraging zero-downtime deployment slots. Built complex TypeScript UI flows (10-page form with global/partial save and custom validation) using Redux + MUI integrated from Figma, and emphasizes quality with RTL/Vitest plus Selenium automation (~95% coverage) and analytics-driven iteration (Heap, Alida, GTM).”

“Backend/data engineer who built an enterprise LLM assistant (AI Genie) at Broadband Insights using a LangChain + GPT-4 + Pinecone RAG pipeline to automate broadband analytics reporting. Developed Python/Dagster ETL processing 10M+ records/day and improved data freshness by 60%, with production-grade scalability patterns (async workers, containerized microservices, Kubernetes) and strong multi-tenant isolation practices.”

“PhD researcher (University of Utah) who built a production RAG-powered Virtual Reality Research Assistant to answer lab research questions with concrete citations. Implemented an end-to-end LangChain pipeline using PyPDFLoader, chunking strategies, OpenAI embeddings, and ChromaDB, with emphasis on grounding to reduce hallucinations and ensure research-grade accuracy. Collaborated closely with a non-technical PhD advisor to scope requirements, manage cost constraints, and demo iterative progress.”

“Frontend engineer who led end-to-end architecture and implementation at Hostclass (startup) using Next.js/TypeScript/Twilio, including a distinctive live-session page with a 3-way screen-sharing capability. Experienced improving messy production codebases by consolidating duplicated workflow logic into reusable hooks and shipping high-risk real-time features with targeted QA and incremental rollouts under tight startup constraints.”

“Full-stack web developer who reports owning both backend and frontend design, including database-first design and jQuery-based web UI work (shared a GitHub project link). Claims to have delivered a project planned for 4 months in just 2 weeks and emphasizes strong personal code quality standards.”

“Product-minded software engineer who owned a Shopify POS app end-to-end at Swym, shipping an MVP and then scaling iteration speed with E2E automation and CI/CD—resulting in a Shopify Badge, Top-5 App Store ranking, and +40% new user acquisition. Also built an ESG insights tool using React/TypeScript + FastAPI with Snowflake and a RAG pipeline, plus microservices patterns (async jobs, queues, DLQs, autoscaling) and internal Metabase/SQL analytics dashboards.”

“Built and shipped a production LLM-powered decision system that replaced a slow, inconsistent manual review process by turning messy text into structured, auditable outputs behind an API. Demonstrates strong end-to-end ownership of reliability and operations (schema validation, retries/fallbacks, latency/cost controls, monitoring for drift) and a disciplined approach to evaluation and regression testing. Experienced collaborating with non-technical reviewers to define success criteria and deliver interpretable outputs that get adopted.”

“Frontend lead on an SME CRM for a bank, building a scalable multi-country/multi-product React/Next.js platform with a config-driven onboarding workflow and multi-role permissions. Emphasizes quality and maintainability through CI gates, a full testing pyramid, and disciplined server-state caching with RTK Query, plus feature-flagged rollouts and data-driven iteration from pilot user feedback.”

“Frontend engineer who has led end-to-end builds of both e-learning and e-commerce platforms in Next.js/React + TypeScript, with a strong focus on scalable component architecture, pragmatic state management (Redux/Zustand), and quality enforcement (linting, conventions, Cypress). Notably pivoted from NextAuth to a custom server-auth flow to support backend-introduced 2FA, and has experience executing fast hotfix rollouts including urgent third-party provider switches.”

“Frontend engineer/lead with deep React + TypeScript experience who has built complex workflow-style interfaces (node/connection editor with debugging panel) and used RxJS to manage intricate event/state flows. Strong focus on scalable architecture (SOLID, separation of concerns), performance at scale (caching, pagination, virtualization), and reliability (memory leak investigation and cleanup), backed by disciplined code review and documentation practices.”

“Primary designer/implementer/maintainer of an open-source JavaScript library for programmatic SSML generation and validation in text-to-speech pipelines. Focused on safety-by-default APIs with vendor-specific extension adapters, strong backward compatibility/deprecation practices, and measurable performance gains by removing redundant validation stages. Emphasizes developer experience through example-driven documentation and systematic community issue triage.”

“Built and deployed a production AI document Q&A (RAG) platform that lets non-technical users query hundreds of PDFs/Word files, cutting search time from hours to seconds. Experienced with scaling retrieval pipelines (chunking, embeddings, vector search, batching/caching) and orchestrating reliable workflows using AWS Step Functions/Airflow with robust retries, monitoring, and fallbacks.”

“Full-stack engineer with end-to-end ownership of a data-heavy financial dashboard module at Brown & Brown Insurance, spanning .NET Core APIs, EF/SQL Server, and React/TypeScript UI. Demonstrates strong focus on performance tuning (indexing, pagination, caching, async) and secure service design (Azure Key Vault, JWT/RBAC) in a microservices context.”

“JavaScript engineer who effectively "maintains" an internal open-source-style React/Node.js shared library used by multiple teams—owning API stability, semantic versioning, CI/testing, logging, and documentation. Demonstrates strong cross-team debugging and change-management skills (schema-driven refactors, feature flags, validation layers) to ship new features without breaking existing workflows, plus a profiling/benchmarking-driven approach to performance.”

“AI/ML engineer with production experience building an enterprise network-fault prediction assistant that combines anomaly detection (Isolation Forest + LSTM) with an LLM layer for incident diagnosis and recommended resolutions. Hands-on with orchestration (Airflow, Prefect, Dagster) to run ETL/ELT and automated training/fine-tuning workflows, and has delivered AI solutions with non-technical stakeholders (retail customer support ticket categorization/response suggestions).”

“Backend engineer at Esurgi focused on real-time clinical workflow systems, improving API reliability, performance, and security. Has hands-on experience with FastAPI/Pydantic, JWT/RBAC and row-level data isolation, plus Kafka-based real-time processing—including fixing duplicate-processing edge cases via idempotency and offset management and rolling out refactors safely with feature flags and staged deployments.”

“Silicon Valley operator with ~30 years of experience as a board member, advisor, VC, founder, and turnaround executive, claiming 50+ venture-backed turnarounds. Has driven outsized outcomes including a $1B Nokia spinout and a 9-figure Jaspersoft exit to TIBCO, and is known for pragmatic, people-and-financials-first operational diagnosis (including CRM forensics) and rapid team scaling via structured hiring pipelines.”

“Full-stack engineer who built an email/SMS marketing platform from the ground up using PHP (Yii2/Laravel) and JS (jQuery/Vue components), including campaign reporting, A/B testing, and extensive ESP/SMS integrations (Mailgun/Mailjet/Twilio plus AWS SES/SNS). Notably scaled the system for very large contact ingestion by migrating from MySQL to ClickHouse and implemented reliability measures like retries, logging, and rate limiting.”

“Early-career candidate with customer service experience and a cybersecurity bootcamp background (vulnerability management). Undergraduate project focused on securing online exams during COVID using identity verification (facial recognition + email/phone code) and 360-degree monitoring to reduce cheating, and they navigated student pushback to enforce integrity.”

“Customer Success Engineer focused on secure customer integrations for web/AI analytics solutions, frequently aligning retail/business teams with security requirements. Has hands-on experience troubleshooting and hardening API-based integrations in AWS (IAM least privilege, VPC/private subnet patterns, CloudWatch/CloudTrail) and delivering repeatable containerized deployments via Bitbucket CI/CD.”

“Backend/architecture-focused player-coach who designed and built two partner-facing data APIs using a contract-first (OpenAPI) governance model in Java (Quarkus/Spring Boot). Strong in technical standards, incident response, and delivery systems—improved reliability under peak load (DB/index fix) and sped up delivery by streamlining PR/review processes while maintaining production stability.”

“Full-stack engineer with enterprise experience at Meta System and DXC, owning end-to-end delivery of a shipment visibility portal (React UI in Liferay DXP + Java/Spring Boot REST APIs) with Dockerized deployments and automated test coverage. Has hands-on AWS work across EC2/Lambda/S3 and multiple databases (DynamoDB, RDS, Neptune, DocumentDB), plus built a Python/Flask data migration platform with validation for correctness and repeatability.”

“Full-stack engineer with healthcare/bioinformatics experience who built a real-time genomic data analysis and 2D visualization feature (React/TypeScript + D3, FastAPI) at University of Utah Health, deploying on AWS ECS Fargate with monitoring and measuring engagement via Google Analytics. Also built AWS Lambda-based ETL pipelines for lab data ingestion using pandas/NumPy with reliability patterns (idempotency, retries, CloudWatch alerting) and drove maintainability improvements through shared component libraries and React hooks.”

“End-to-end engineer focused on AI-native enterprise systems, including a production generative knowledge platform using RAG + semantic search over internal documentation (React, Python/Flask, GPU-hosted NLP models, Pinecone) with strong CI/CD and observability. Reports concrete outcomes including 40% faster knowledge access and ~75% employee adoption, and has led incremental cloud-native modernization using feature flags, parallel runs, canary releases, and regression testing.”