Vetted Selenium Professionals

Denvinn Magsino

Screened ReferencesModerate rec.

Mid-level Software Development Engineer in Test specializing in CI/CD and web automation

Los Angeles, CA4y exp

“QA automation engineer with ad-tech domain experience (Prebid.js wrapper-based services) who built an end-to-end Python automation framework using Playwright to validate wrapper settings, auction request/response, and analytics payloads. Uses Jenkins-driven CI reporting and feature-categorized regression runs to quickly isolate revenue-impacting defects and coordinate fast fixes with developers.”

“Embedded/real-time robotics-style engineer with hands-on STM32 development, sensor integration, and low-level drivers, focused on deterministic control behavior. Demonstrated systematic debugging of jitter/latency by instrumenting the sensing-to-actuation pipeline and eliminating blocking via interrupts, hardware timers, and DMA; also designs asynchronous, message-based interfaces for distributed real-time components. Familiar with ROS/ROS2 concepts (nodes/topics/callbacks) though not yet deployed a full production ROS system.”

“Backend/full-stack engineer building complex internal platforms and customer-facing demos at the intersection of infrastructure and product. Shipped a no-code Product Lifecycle Manager for manufacturing (3 manufacturers, 1000+ evolving tests) using AWS S3/SQS ingestion and extensible Postgres (EAV+JSONB) with end-to-end traceability. Also built a FastAPI-based company data intelligence platform with Okta-secured RBAC and an LLM/MCP layer for ChatGPT-like analytics over enterprise data sources.”

“Product-focused full-stack engineer with Walmart and Dell experience who built and shipped a real-time engagement dashboard end-to-end (Kafka Streams, Spring Boot, React/TypeScript/D3) used daily by business teams, moving them from next-day reports to real-time decisioning. Strong in performance/reliability (Redis caching cut latency ~40%, 90%+ test coverage, Prometheus/CloudWatch monitoring) and production operations on AWS/EKS including handling a cascading failure from a memory leak with zero-downtime rollback and redeploy.”

“Full-stack engineer with production experience building and owning high-traffic e-commerce checkout flows in Next.js (App Router) + TypeScript across microservices (REST/GraphQL). Demonstrated measurable performance wins (30% checkout improvement; 85% initial load reduction at 20th Century FOX) and strong production rigor (APM/logs, CloudWatch, Postgres indexing + EXPLAIN ANALYZE), including offloading PDF generation to AWS Lambda.”

“LLM/agent engineer who shipped a production RAG-based recommendation + explanation system that replaced a traditional recommender stack, delivering ~20% CTR lift (and +8% after a reliability iteration) with strong cold-start performance. Demonstrates strong production rigor: schema-constrained generation, typed tool calling, explicit state/orchestration, deep monitoring/feedback loops, and safe integration with messy ERP inventory/order data using normalization, idempotency, and conflict-resolution guardrails.”

“Data engineer/backend engineer who owns large-scale, real-time event pipelines on AWS end-to-end, including a petabyte-scale CDC ingestion flow from multiple Postgres DBs into Redshift. Re-architected a legacy DynamoDB+S3 approach into a Delta Lake + DuckDB/PyArrow-compatible design, improving performance dramatically (e.g., ~600s to ~10s for 1k records) and increasing reliability at high file volumes.”

Mithilesh Gaurihar

Screened

Mid-Level Software Engineer specializing in Java microservices and cloud-native systems

USA4y exp

“Full-stack engineer (SAP Labs experience) who built an end-to-end, real-time fraud detection system on Java 11/Spring Boot microservices with Kafka event streaming and a React/Redux analytics dashboard with WebSocket updates. Demonstrated strong production ownership by diagnosing a critical memory leak with Prometheus/CloudWatch + heap dumps and improving performance with Redis caching (40% faster queries), while also modernizing deployments via Kubernetes, Jenkins CI/CD, and Terraform.”

Advitha Bawgi

Screened

Junior Full-Stack Software Engineer specializing in cloud-native microservices

India1y exp

“Backend engineer with hands-on IoT and AI product work: built a decoupled Raspberry Pi + AWS IoT Core weather monitoring backend and a Dockerized FastAPI LLM service on AWS ECS using OpenAI/HuggingFace with an emerging RAG layer. Also delivered measurable performance gains at DAZN by redesigning event-driven/serverless ingestion (SNS, S3->Lambda->DynamoDB), cutting latency ~30% and boosting throughput ~25% while automating ~90% of manual sync work.”

Jahnavi Bellapukonda

Screened

Mid-Level Software Engineer specializing in full-stack web and cloud systems

Remote, USA3y exp

“Full-stack engineer with strong data engineering and privacy-domain experience, having owned an automated Data Subject Rights (DSR) processing pipeline end-to-end across Azure SQL and GCP (GCS/BigQuery). Emphasizes production reliability via idempotency, validation checkpoints, structured logging/monitoring, and safe CI/CD-driven deployments, and has also built React+TypeScript + Node/Postgres web apps with scalable, maintainable architecture.”

Mounika Gunturu

Screened

Senior Python Full-Stack Developer specializing in cloud-native microservices and data platforms

New York, NY9y exp

“Backend/data engineer from Oliver Wyman who built and ran production Python (FastAPI) services on AWS (ECS/Lambda/API Gateway) supporting risk modeling and regulatory reporting. Strong in reliability/observability, Glue-based ETL with data quality controls, and legacy SAS-to-Python modernization with rigorous parity validation; also demonstrated measurable SQL performance wins and cost-control improvements in serverless scaling. Based in Raleigh, NC and can travel onsite for important Bethesda-area meetings.”

Neeshma Narahari

Screened

Mid-level Software Developer specializing in backend microservices and cloud platforms

Irving, TX6y exp

“Full-stack product engineer with strong React and TypeScript depth who has owned dashboard features end-to-end, from UI architecture and rendering optimization through Spring Boot APIs and database query tuning. Particularly compelling for startup or high-growth teams: they’ve shipped 0→1 internal operations platforms, prioritized MVP workflows effectively, and iterated post-launch using user feedback, logs, and usage metrics.”

“Built and deployed a production LLM/RAG document automation system for business documents (contracts/claim forms) that extracts schema-validated JSON, generates grounded summaries/Q&A, and integrates into transaction systems via APIs. Emphasizes real-world reliability: hallucination controls, layout-aware parsing with OCR fallback, Step Functions-orchestrated workflows with retries/timeouts, and human-in-the-loop review designed in close partnership with operations and claims stakeholders.”

“Built and productionized an NLP-powered customer support assistant at JPMorgan Chase for digital banking, focused on reducing response time for repetitive client queries. Strong in real-world AI deployment challenges—sensitive data handling, low-latency FastAPI services, and AWS/Kubernetes operations with CI/CD—plus a metrics- and guardrails-driven approach to reliable AI workflows.”

“Backend engineer with experience at Comcast and in healthcare/pharmacy automation (PrimeRx), building Python/Flask services that orchestrate large-scale batch workflows (Airflow) and high-throughput event processing (Kafka). Demonstrated measurable performance wins (cut provisioning latency to ~150–200ms) and strong multi-tenant isolation strategies (Postgres RLS, partitioning), plus practical integration of ML model outputs into production systems with validation and fallback controls.”

“Backend engineer who has led major platform evolution to cloud-native microservices (Spring Boot on AWS with Terraform) and built scalable, secure FastAPI APIs. Demonstrates strong production rigor with metric-driven validation, canary/phased rollouts, and incremental migrations using shadow traffic/feature flags/parallel writes—achieving faster deployments, fewer incidents, and zero-downtime traffic spikes and migrations.”

“QA automation engineer with experience at Amazon Game Studios owning an end-to-end automated scale testing suite that simulates high-concurrency gameplay and captures performance telemetry. Improved coverage by bypassing hours of gameplay via programmatic state setup, enabling repeatable 4000-player dungeon-entry tests that exposed a messaging-queue bottleneck fixed before release. Also built maintainable Selenium/pytest UI automation with CI gating, reporting, and flake-reduction patterns.”

“Software engineer in the mortgage/financial services domain (Freddie Mac) who builds end-to-end loan origination and credit risk capabilities using Spring Boot microservices, Angular dashboards, and data pipelines. Delivered measurable impact (30% reduction in underwriting turnaround time) and emphasizes production reliability/compliance with strong guardrails, observability, and evaluation loops for risk scoring systems.”