Vetted Redis Professionals

“Built and shipped an AI-powered journaling app feature that analyzes user text for emotions in real time, owning everything from React/TypeScript UX (dynamic theming + Framer Motion) to a FastAPI backend integrating Hugging Face. Has hands-on production experience deploying Dockerized services on AWS (EC2/RDS/S3/CloudWatch) with GitHub Actions CI/CD, and resolved a real latency/scaling incident by converting blocking external API calls to async with retries/timeouts.”

“Frontend engineer who led the Cariveco frontend end-to-end, establishing a scalable React/TypeScript architecture with a design system, CI-driven quality gates, and strong performance practices (Lighthouse, code-splitting, caching). Experienced building complex dashboards with role-based views and real-time data using Redux + RTK Query, and shipping major features quickly with automated testing, feature flags, and Sentry monitoring.”

“AI/backend engineer who has built and scaled production LLM-powered SaaS features (document assistant + compliance review agent) on a Node.js/TypeScript + Postgres/Redis stack deployed to GCP Kubernetes. Demonstrates strong production reliability chops—async queueing, autoscaling, observability, and database tuning—with quantified wins (p95 latency -60%, query 4s to <200ms) and robust AI guardrails (strict RAG, schema validation, citations, HITL).”

“Full-stack engineer with experience delivering an end-to-end NIH application using Angular and scalable .NET Core microservices backed by MySQL. Has hands-on depth in complex approval/workflow implementations (RBAC + workflow engine) and performance tuning for million-record, data-driven systems, plus 5 years with Java/Spring Boot microservices and React.”

“Built and deployed a production LLM-powered recruitment chatbot that automates key recruiting steps (sourcing, candidate engagement, screening). Strong in agent orchestration with LangGraph, including guided graph-based workflows, context-aware routing, and reliability measures like clarifying steps plus human-in-the-loop evaluation.”

“Application security engineer/advisor with hands-on experience securing AWS-based, containerized services and embedding SAST/DAST/SCA and container scanning into GitHub/GitLab CI/CD. Drove measurable outcomes (50% faster vuln triage, 40% fewer misconfigs) and has deep operational troubleshooting experience in Kubernetes (agent failures due to CPU throttling/network policies), plus pragmatic strategies to reduce developer friction and handle API rate limits.”

“Backend/ML engineer with deep fintech and marketplace experience: built a real-time financial analytics + algorithmic trading platform (Python/Postgres/Kafka/Redis) and drove major DB performance wins (10x faster analytics; sub-10ms response consistency). Also shipped an end-to-end ML recruitment matching platform (scraping/ETL/modeling/Django deployment) with reported 92% matching accuracy, and emphasizes production reliability via monitoring, blue-green deploys, and robust workflow error handling.”

“Backend/data engineer with hands-on production experience building a FastAPI Python service on AWS for real-time AI workflows (Postgres/Redis, containers behind API Gateway) with strong reliability practices (JWT auth, timeouts/retries, health checks). Has delivered AWS infrastructure using Terraform + GitHub Actions across environments, built Glue ETL pipelines into Snowflake with idempotent recovery, and modernized legacy batch workflows via parallel-run parity validation and phased cutovers.”

“Frontend engineer (~4 years) who led an admin dashboard for potato farmers end-to-end, integrating real-time and historical weather data to drive disease-severity predictions. Built scientifically validated calculation pipelines (FAO Penman-Monteith, late blight models), rigorous Cypress/unit testing, and print/PDF-ready reporting, while optimizing performance and API load with debouncing, caching, and feature-flagged rollouts.”

“New-grad software engineer who built a real-world smart-city traffic camera/operations dashboard pitched to Peachtree Corners, GA, integrating Bosch cameras with an MQTT/Node-RED/InfluxDB pipeline and Grafana visualizations. Implemented rule-based alerts (including SMS dispatch for janitorial cleaning) and improved production reliability with queuing, redundancy, monitoring, and load testing, reaching ~99% message delivery. Actively seeking onsite, customer-facing roles with travel.”

“Early-career full-stack engineer who has not yet shipped a professional customer-facing product but has built sophisticated AI-driven systems in personal/academic work, including a multi-tenant AI knowledge base (async ingestion, pgvector semantic search, SSE real-time updates, knowledge graphs) and an AI-powered code review assistant designed to process thousands of jobs via Redis/BullMQ.”