Vetted Redux Professionals

“Backend engineer with experience at JPMorgan Chase and Walgreens, owning transaction-processing and prescription data flow systems in regulated environments. Brings strong hands-on depth in Spring Boot microservices, Kafka, Redis, Kubernetes, observability, and production incident resolution, plus practical experience integrating OpenAI-powered workflows with validation and fallback safeguards.”

“Full-stack web developer with hands-on ownership of products from requirements through launch and maintenance, building across React and Node.js. Stands out for balancing product usability with technical performance, including API/database optimizations that improved performance by about 30% and shipping real-time dashboard features with scalable frontend/backend tradeoffs.”

“Backend/platform engineer with deep payments experience who built and operated a real-time transaction routing service end-to-end on AWS (Spring Boot, PostgreSQL/RDS, Redis, Kubernetes), delivering ~40% latency reduction and 99.99% uptime via strong resiliency and observability practices. Also productionized an internal LLM-powered RAG knowledge assistant with guardrails and a user-feedback-driven evaluation loop, and has led incremental monolith-to-microservices modernization using Strangler Fig and shadow traffic.”

“Salesforce-focused candidate with hands-on experience delivering Service Cloud automation, including entitlement/SLA escalation workflows, and building multi-component Lightning UI frameworks. Brings a mix of native-platform design, custom Apex extension, LWC architecture, and legacy Aura maintenance experience.”

“Backend engineer from Palantir who built and productionized an enterprise LLM-based document intelligence/search platform, evolving it into a hybrid lexical+vector retrieval system. Emphasizes reliability and cost control via strict LLM gating, robust fallback paths, and evaluation frameworks (e.g., MMLU/BLEU), plus disciplined migration practices (feature flags, dual-writes, shadow reads) to ship changes safely at scale.”

Changhee Lee

Screened

Mid-level Software Engineer and Product Manager specializing in AI and financial data platforms

Remote4y exp

“Full-stack engineer with deep Next.js App Router + TypeScript experience who has shipped and owned production features in a fashion/wardrobe/resale domain. Demonstrated measurable impact across the stack: +25% engagement, 30% faster load times, 40% fewer errors, plus durable Temporal workflows and Postgres analytics/query tuning for real-time dashboards.”

“Product-minded software engineer with experience shipping AI-powered financial insights (spend forecasting, cashflow, credit optimization) and building real-time analytics systems using React/TypeScript and FastAPI. Has designed microservices with RabbitMQ/gRPC and strong observability (Prometheus/Grafana/OpenTelemetry), and also built an internal Figma plugin adopted by designers that reduced export time by 50%.”

“Backend-focused engineer who uses AI pragmatically as a force multiplier rather than a substitute for engineering judgment. They stand out for applying structured, agent-style workflows to code generation, debugging, and production log analysis while maintaining strong emphasis on correctness, performance, and reliability in backend and microservices environments.”

“Financial systems engineer who built an automated rebalance-day order reporting and analytics tool on kdb+ pipelines, cutting a high-visibility manual process from 2–3 hours to ~2 minutes and expanding it from North America to EMEA/APAC. Also proposed an early production RAG-based incident knowledge assistant trained on ServiceNow postmortems, with guardrails to scope retrieval by application.”

Vindhya Naidu

Screened

Mid-level Backend Software Engineer specializing in Java/Spring microservices and FinTech

Austin, TX5y exp

“Backend engineer with Apple experience who owned production platform improvements end-to-end, including a Redis caching layer that cut API latency ~35–40% and reduced DB load. Has hands-on on-call/incident response and observability (CloudWatch), plus experience scaling Docker/Kubernetes microservices and operating Kafka-based telemetry pipelines with schema evolution, deduplication, and replay/backfill handling.”