Vetted Selenium Professionals

“Full-stack engineer who has owned customer-facing AI recommendation and analytics dashboards end-to-end (backend APIs/data processing through React UI, deployment, and monitoring). Demonstrates strong systems thinking around scaling microservices—using observability, caching, async workflows, and resilience patterns—and also built an internal ops dashboard that became the default tool for on-call incident reviews.”

“Built a production AI agent for phishing fraud detection using n8n orchestration, Claude (Sonnet 4/MCP), VirusTotal, and JavaScript formatting to generate and deliver email-based reports via Gmail. Has experience evaluating detection accuracy against known examples, iterating via feedback, and presenting AI solutions to non-technical teams.”

“Backend/platform engineer who owned high-volume Java/Spring Boot microservices on AWS (Kafka + RDS/DynamoDB) and has hands-on experience debugging complex production latency incidents across DB, JVM/GC, and async consumers. Also shipped applied AI features for ops, including an LLM-powered log analysis assistant and an incident-response agent with strong safety guardrails (schema-validated tool use, retries/backoff, and human-in-the-loop escalation).”

Priyanshu Maurya

Screened

Mid-level Data Scientist specializing in insurance, finance, and healthcare analytics

New York, NY3y exp

“Built and productionized LLM-driven sentiment scoring for earnings call transcripts at Goldman Sachs, replacing legacy NLP to deliver a cleaner trading signal while managing latency/cost via batching, caching, and distilled models. Also implemented an Airflow-orchestrated fraud modeling pipeline at MetLife with drift-based retraining and SageMaker deployment, and has a disciplined evaluation/rollout framework for reliable AI workflows.”

“Built and shipped a production LLM-powered internal developer tool that accelerated code reviews by about 30% while maintaining reliability through modular orchestration, validation, and monitoring. Demonstrates strong practical depth in agent architecture, backend workflow orchestration, and observability for non-deterministic AI systems, with concrete examples of reducing agent errors by 60%.”

“Interned at Paycom and shipped a productionized ML/AI system that automatically regenerates XPath selectors to self-heal Selenium UI tests when the DOM changes. The pipeline handled 1,000+ failing tests/hour with ~90–95% auto-fix accuracy, using confidence thresholds, human-in-the-loop fallbacks, logging/dashboards, and retraining loops to manage distribution shift and maintain reliability.”

CHIRAG ARORA

Screened

Senior Backend Software Engineer specializing in microservices and cloud platforms

San Jose, CA9y exp

“Backend engineer with PayPal experience building a high-reliability onboarding API platform (Java/Spring Boot) integrating KYC/compliance and serving 1M+ users annually. Also shipped an internal LLM-driven developer tool that automates PR review insights and OpenAPI documentation with rigorous evaluation, schema-bound guardrails, and production observability.”