Vetted React Testing Library Professionals

“Backend/data engineer with hands-on production experience across Python/Flask microservices and AWS serverless/data platforms (Lambda, DynamoDB, S3, Glue/PySpark). Demonstrated strong reliability and operations mindset (JWT/RBAC, retries/timeouts/circuit breakers, CloudWatch/SNS alerting) and measurable performance wins (SQL report runtime cut from 10 minutes to 30 seconds). Seeking ~$150k base and cannot travel for onsite meetings for the next 5–6 months due to family medical constraints.”

“Frontend engineer focused on high-scale React + TypeScript dashboards, including an internal Instagram creator/agency analytics dashboard handling extremely large datasets (1–2TB) with virtualization and performance profiling to maintain ~60fps UX. Experienced in modern state management (Redux Toolkit/RTK Query), modularizing legacy codebases into shared component libraries (Storybook), and shipping fast with feature flags plus automated QA (Playwright/Selenium).”

“Backend/data engineer with hands-on production experience building Python/Django APIs on PostgreSQL and delivering AWS serverless + containerized architectures (API Gateway/Lambda, IaC, CI/CD, secrets/config). Has operated AWS Glue pipelines ingesting S3 log/3rd-party data with schema evolution monitoring, modernized legacy batch logic into API-based services via parallel-run parity testing, and improved Postgres query performance by several seconds; prefers fully remote work and targets $120–130k base.”

“Frontend engineer who has led architecture and delivery of large, data-driven React/TypeScript interfaces used by thousands of users, with strong emphasis on scalable structure, performance, and automated quality gates (CI/CD, Jest/Cypress). Recently building a resume screening application for McMaster University students and has experience shipping role-based (RBAC) features with tight cross-functional collaboration and PR-based QA deployments.”

“Backend engineer with Accenture and EY experience building multi-tenant financial/compliance platforms in Python/Flask. Strong in performance and scalability work across SQLAlchemy/PostgreSQL (EXPLAIN ANALYZE, indexing, N+1 fixes) and in reliability improvements using Celery + Redis. Has integrated external AI model APIs for document extraction/invoice validation with robust background processing, retries, and output cleaning.”

“Backend engineer who evolved Coca-Cola bottlers' Trade Promotion Optimization platform at Coke One North America, building domain-focused microservices in Node.js and Python (Flask/FastAPI) with PostgreSQL. Experienced in multi-tenant security (OAuth2/JWT, RBAC, row-level scoping by bottler/region), API contract/versioning discipline, and Azure DevOps-driven incremental rollouts with strong observability.”

“Backend/data engineer who has built production AI video generation services on AWS using a hybrid serverless + container architecture (FastAPI, Lambda, ECS, Postgres/Redis) with strong reliability practices (auth, retries/timeouts, structured logging, CloudWatch + Slack alerting). Also delivered AWS Glue ETL pipelines with schema evolution handling and modernized a legacy SAS healthcare reporting workflow to Python with parity validation and parallel-run migration.”

“Backend/platform engineer in fintech/payments (NexaBank/NextBank/Nexon Bank) who has built Kafka-orchestrated Java/Spring Boot microservices around a PostgreSQL double-entry ledger. Led production-critical reliability work preventing duplicate payment postings via idempotency and offset sequencing fixes, and shipped real-time ML fraud scoring (Python model API + Redis caching) with rigorous evaluation/monitoring (Prometheus) and workflow automation for dispute resolution.”

“Backend engineer with fintech/transaction-processing experience who built and optimized a Spring Boot + PostgreSQL + AWS service handling money transactions, resolving peak-traffic latency via query/index and connection pool tuning. Shipped an LLM-driven risk-flagging workflow integrated via a FastAPI Python service, owning prompt design, validation guardrails, monitoring, and human-in-the-loop escalation to reduce false positives and improve precision over time.”

“AI/LLM engineer with crypto/social-data domain experience who built an end-to-end AI trading signals and analysis backend using Next.js, Inngest, Gemini, and Supabase, including real-time progress UX and robust rate-limit/reliability handling. Also published an MCP SDK on NPM for authenticated agent tool access and built autonomous Twitter-based AI agents; strengthened reliability at LunarCrush by adding CI-gated E2E testing across web and mobile (Cypress/Maestro).”