Vetted Idempotency Professionals

“Full-stack engineer who has owned React/TypeScript + Spring Boot dashboard products end-to-end, including real-time performance/alerts and data aggregation across services. Strong in shipping MVPs quickly with feature flags, automated testing and CI/CD, and using monitoring/click-path analytics to prioritize work—achieved a 40% page-load reduction. Experienced operating microservices with RabbitMQ at scale, addressing retries/idempotency/observability and fixing duplicate-processing incidents with idempotent consumer patterns and DLQs.”

“Python backend engineer who owned an end-to-end Django/DRF authentication and account-management module (JWT, RBAC, email verification) and optimized token validation performance. Has hands-on Kubernetes + Helm delivery with GitOps via ArgoCD (multi-environment app-of-apps, drift detection/rollback) and has supported a cloud-to-on-prem migration using staged testing and phased cutover. Also built and scaled a Kafka-based real-time user activity tracking pipeline with reliability and backpressure controls.”

“Backend engineer with airline operations domain experience who modernized flight-ops systems from batch updates to real-time streaming on AWS (Kafka + Spring Boot microservices), improving latency and stability through metric-driven tuning and idempotency. Also shipped a production LLM decision-support component using RAG over operational logs and internal procedures, with strong guardrails and an evaluation/regression loop to reduce hallucinations and enforce grounding.”

“Data engineer with healthcare/clinical trial domain experience who owned a 100TB+/month AWS pipeline end-to-end (Glue/S3/Redshift/Airflow) and drove measurable outcomes (20% lower latency, 99.9% reliability, 40% less manual reporting). Also built production data services and API-based ingestion on GCP (Cloud Run/Functions/BigQuery) with strong validation, versioning, and safe migration practices, and launched an early-stage RAG solution (LangChain + GPT-4) for researchers.”

“Data/analytics engineer focused on finance and e-commerce integrations, building end-to-end pipelines and services across Odoo, QuickBooks, Snowflake, and Tableau. Replaced a costly third-party Walmart connector with a serverless AWS Lambda pipeline deployed via Terraform/GitHub and monitored with CloudWatch/Datadog, and shipped a bi-directional Odoo↔QuickBooks invoice sync with distributed locking plus Slack-based finance approvals.”

“Built and shipped an AI-driven interview evaluation pipeline at SeekOut that automated recruiter screening via a multi-stage LLM agent workflow (.NET backend, RabbitMQ orchestration, Python workers). Emphasizes production-grade reliability (idempotency, retries, strict JSON/schema validation), strong observability with OpenTelemetry, and measurable efficiency gains including ~40% reduction in token usage/cost.”

Vivekananda Reddy

Screened

Mid-Level Full-Stack Software Engineer specializing in Java, React, and AWS

Dallas, TX4y exp

“Backend engineer focused on cloud-native microservices on AWS, owning Python/Flask ingestion services integrated with S3/Lambda and deployed via Docker/Kubernetes with CI/CD. Has led phased migrations from manually managed EC2 setups to automated CloudFormation + pipeline-driven releases, and designed event-driven near-real-time pipelines with idempotency, retry/backoff, and strong observability.”

Xin Li

Screened

Staff Software Engineer specializing in distributed systems and high-concurrency APIs

Santa Clara, CA17y exp

“Full-stack engineer in an insurance + telematics org who built a 0→1 multi-agent, AI-driven mobile regression execution system integrating Jira and n8n, emphasizing determinism (schema-validated outputs), traceability (state-machine style step archives), and scalable device scheduling. Also designed an event-driven microservices architecture using Kafka with standardized API/event contracts and has hands-on incident response experience improving resilience via rate limiting, circuit breaking, caching, and idempotency.”

Kavya Myakala

Screened

Mid-level Frontend Developer specializing in security analytics dashboards

NJ, USA4y exp

“Built and shipped production LLM agents including an end-to-end customer support resolution system (99.9% uptime target) that improved customer satisfaction by ~18% and reduced the need to scale support headcount. Demonstrates strong agent engineering fundamentals—tool-based orchestration, schema-first structured outputs with deterministic validation, and robust eval/monitoring loops—plus experience integrating agents with messy ERP data using canonical normalization and safe fallbacks.”

“Built practical automation systems spanning an NLP-based news classification pipeline and a WhatsApp interaction agent. Shows strong instincts around production reliability—using structured outputs, schema validation, idempotency, retries, and clarification flows to prevent bad actions in real-world messaging workflows.”

“Fullstack engineer with strong backend depth who has owned complex digital banking modernization work end-to-end, spanning React UI workflows, Spring Boot microservices, API design, and event-driven integrations. Stands out for balancing technical architecture with user clarity, especially in ambiguous environments where stakeholder feedback reshaped workflows after launch.”

“Full-stack engineer with a strong builder mindset who has shipped both enterprise workflow software and AI-powered assistant platforms. They combine React/TypeScript and Node.js depth with hands-on experience in LLM/RAG systems, vector search, and reusable MCP-based agent infrastructure, and have delivered customer-facing products for enterprise operations teams including 40+ features across two products.”

Bhanu Akepogu

Screened

Mid Software Engineer specializing in backend, full-stack, and AI systems

USA3y exp

“Full-stack engineer with 3+ years of backend and frontend experience who has built production AI products for enterprise document and policy workflows. Stands out for owning end-to-end systems that combine React, FastAPI, RAG, vector search, and AWS deployment, with measurable impact including 65% less manual review time and significantly faster knowledge-query resolution.”

“Frontend engineer with experience building data-intensive, near real-time React/TypeScript applications in credit reporting and logistics tracking. Stands out for performance-focused architecture across dashboards and map-based products, including large dataset optimization, profiling, and Mapbox visualizations with live asset tracking.”