Vetted Selenium Professionals

“Software engineer with experience at Wipro and Tylmen Tech owning customer-facing onboarding and real-time features end-to-end (React + Spring Boot) and building TypeScript/React apps backed by Node.js microservices (MongoDB, RabbitMQ). Strong in production reliability and fast iteration: feature-flagged rollouts, idempotent APIs/consumers, DLQs, and SLO-driven incident tooling, including an internal QA & release dashboard adopted by engineering and support teams.”

“Frontend engineer who has led enterprise-scale UI delivery end-to-end on a microservices platform, designing modular Angular SPAs (v12-17) tightly aligned to Spring Boot REST APIs. Emphasizes quality and release velocity through layered testing (Karma/Jasmine), CI/CD automation (Jenkins/Azure DevOps), performance tuning with RxJS/lazy loading, and incremental rollouts with close product/design/QA collaboration.”

“Backend engineer who replaced an Excel-heavy forecasting workflow with a secure, auditable FastAPI system (React UI + relational model + async workers), emphasizing deterministic processing, idempotency, and versioned ledger-style ingestion. Led a monolith-to-FastAPI migration at Bounteous using a strangler approach, feature-flagged incremental rollout, and data reconciliation/shadow-compare to protect integrity while scaling onboarding workflows.”

“AI engineer who built a production e-commerce system that analyzes product images alongside sales and demographic data to generate actionable creative recommendations, now used by 20+ clients. Also built orchestrated document/agent pipelines (Airflow, LangGraph) including a compliance drift detector auditing 401 compliance documents, with an emphasis on traceability, logging, and production integration.”

“Frontend engineer at Mailchimp who leads end-to-end React/TypeScript features on the in-app homepage, including onboarding and campaign discovery components. Demonstrated measurable performance impact by cutting homepage LCP by ~2.5s and successfully shipped a major feature on an accelerated deadline using structured QA and staged rollout.”

“Frontend-focused engineer with full-stack experience who modernized a legacy HR platform (CoffeeScript/Marionette) by migrating key UIs to React/Redux and adding TypeScript for robustness. Built an internal client monitoring tool end-to-end with a microservices-oriented approach and strong testing practices (Jest/Selenium), and also led a major GraphQL v1→v2 migration delivered incrementally over ~6 weeks while optimizing Django/MySQL/DynamoDB performance.”

“Software engineer with strong full-stack and platform experience (TypeScript/React/Node.js) who has built real-time analytics dashboards and microservices using RabbitMQ. Demonstrates production-minded decision-making under launch pressure (manual fallback for payment-impacting third-party API issues) and has delivered internal DevOps tooling that automates compliance checks via GitHub/Jira integrations.”

“Full-stack engineer/product owner who built and scaled a customer-facing job application portal (Skillbridge) using TypeScript/React and Spring Boot/MongoDB, optimizing search performance with indexing, caching (Redis), and payload/lazy-loading improvements. Also built an internal AI-driven analytics dashboard for Salesforce operations using OpenAI sentiment analysis, achieving 70% reduction in manual analysis and driving adoption through demos and iterative feedback.”

“Cloud-native integration engineer (Oracle/OCI) with strong production deployment and incident-response experience, including API gateway rollouts, observability (Prometheus/Grafana), and multi-layer debugging for payments systems. Built Python/FastAPI microservices and automation for customer-specific reporting and data sync, and has delivered major performance gains (45 min to <10) plus reliability improvements (MTTD reduced 40%+) through monitoring, playbooks, and resilient integration patterns (streaming/queuing, retries, secure tokens, VPC peering).”

“Backend engineer at Cerebrone.ai building cloud-native Flask microservices for an AI-driven automation platform on GCP (Cloud Run/App Engine), including dedicated inference services integrating OpenAI and internal ML pipelines. Demonstrated strong performance and scalability wins across Postgres/SQLAlchemy optimization, multi-tenant (healthcare/HIPAA-grade) data isolation, and high-throughput background processing with Celery/Redis/RabbitMQ, with multiple quantified latency/CPU/throughput improvements.”

“Built a production RAG-based “unified assistant” that consolidates siloed company documents into a single chatbot while enforcing fine-grained access control via RBAC/metadata filtering with OAuth2/JWT. Experienced orchestrating LLM workflows with LangChain/LangGraph + FastAPI (async + caching) and measuring performance via retrieval accuracy and response-time SLAs. Also delivered a churn analytics solution with dashboards and automated retention campaigns using n8n.”

“Backend engineer who led major modernization efforts at GoDaddy, migrating legacy Perl services to Python/FastAPI with an incremental rollout strategy, containerization (Docker/Kubernetes), and CI/CD (Jenkins/GitHub Actions). Strong focus on secure, reliable API design (JWT, RBAC, PostgreSQL row-level security), rigorous testing, and data integrity—plus experience hardening an automated web-scraping pipeline against changing site structures and downtime.”

“Backend/AI engineer who built a Spring Boot timesheet API on AWS (Postgres, Docker, Nginx) used by hundreds of daily users and resolved severe deadline-driven latency/5XX incidents via query optimization, connection pool tuning, and Redis caching. Also shipped application-layer LLM features (Mistral + LangChain chatbot) and designed a Planner/Executor/Verifier troubleshooting agent with verification-based guardrails to prevent hallucinated root-cause analyses.”

“Deloitte engineer who built and shipped AI-powered, Kafka-driven workflow automation for transportation/document processing, including LLM-based semantic search. Strong in production reliability (idempotency, offset management, retries), observability (Datadog/CloudWatch), and database performance tuning (PostgreSQL/Flyway), with measurable latency improvements.”

“Backend engineer on Morgan Stanley’s trade risk and compliance platform, building Java/Spring Boot microservices that validate equity and fixed-income trades at multi-million-events/day scale. Shipped an LLM-assisted trade exception analysis feature using RAG over internal policy documents and trade history, with production-grade guardrails (confidence thresholds, audit logs, human-in-the-loop) and measurable performance wins (~30–35% faster reporting) through PostgreSQL tuning and Redis caching.”

“Enterprise CSM/program lead specializing in AI-powered search and workflow automation, who owned an end-to-end generative AI chatbot rollout that replaced manual Excel-based RFP processes and achieved 4.5/5 CSAT. Leveraged outcomes to expand the account into two additional use cases (tripling ARR) and has a track record of influencing product priorities (UI personalization) and driving Voice AI expansions tied to operational support workflows.”

“QA automation engineer who built and maintained a Selenium WebDriver + Java hybrid framework (data/keyword-driven) using POM, TestNG, and Maven, and integrated it into CI with PR gating and nightly regression. Strong focus on stabilizing flaky tests (wait strategies, locator robustness, test data control) and caught a critical UI/backend mismatch that could have caused duplicate money transfers before release.”

“Azure cloud platform engineer with strong enterprise Linux operations background who designs multi-region HA/DR on Azure (and AWS) using Azure Site Recovery, Traffic Manager, AKS autoscaling, and geo-replicated Azure SQL. Built secure Azure DevOps CI/CD pipelines for .NET/Python microservices to AKS/VMs and provisions full environments via Terraform modules with remote state, drift checks, and staged rollouts; has not directly owned IBM Power/AIX at scale.”

“Built Nexthire-AI, shipping an end-to-end LLM-powered resume–job description matching product (React + Node.js) using embeddings and retrieval to generate match scores and skill-gap recommendations. Improved post-launch engagement by making feedback cleaner and more actionable, and added production guardrails (validation, timeouts, fallbacks) to handle messy resume formats and AI API instability.”

“QA automation engineer who owned end-to-end test automation for a web-based enterprise application, building and scaling suites in Selenium/Java/TestNG and Cypress/JavaScript. Strong in CI/CD integration with PR gating and actionable reporting, and has prevented high-severity auth/session regressions by catching role-based login/token issues early via automated CI runs.”

“Software engineer with payments-domain experience (Visa) building real-time transaction monitoring and analytics systems. Strong end-to-end ownership across Spring Boot/Kafka microservices, PostgreSQL modeling, and AWS/Kubernetes operations, plus React+TypeScript dashboards—focused on low-latency processing, secure APIs, and zero-downtime production releases.”