Vetted Automated Testing Professionals

Shantrisse Broughton

Screened

Entry-Level QA Tester specializing in game and web/app testing

1y exp

“Game QA tester with experience on multiple commercial (non-AAA) titles including Amateur Surgeon 4 (separate iOS/Android test plans), Desync, and Rick and Morty VR. Focuses on gameplay/performance risks and is known for clear, visual bug reporting (screenshots and hand-drawn visuals) to help teams reproduce and understand issues; worked in a structured QA org where supervisors handled developer-facing verification tracking.”

John Chance

Screened

Senior Machine Learning Engineer specializing in conversational AI and healthcare ML

Greenwood, LA9y exp

“ML/AI engineer with hands-on ownership of both classical recommender systems and safety-sensitive LLM agent platforms. They combine production MLOps depth with behavioral health domain experience, including clinical safety validation, explainability, and multi-agent orchestration, and cite measurable impact in both business metrics and latency reduction.”

Jeffrey Ren

Screened

Mid-level Full-Stack Software Engineer specializing in SaaS and AI-enabled web applications

Henderson, NV5y exp

“Full-stack engineer who led an end-to-end rebuild of a service-agent case management app (React SPA + backend/DB updates) and added Datadog monitoring, improving agent throughput by ~1 case/hour and saving roughly $15K/month. Experienced in incremental legacy modernization (including moving a legacy React frontend toward a Rails-based approach) with heavy unit/E2E testing and strong cross-team stakeholder communication.”

“Full-stack engineer with 8 years of experience spanning regulated healthcare IoT and enterprise security SaaS. Has worked on a high-growth healthcare equipment platform and DigiCert's certificate lifecycle management product, combining hands-on React/Node.js development with compliance, auditability, and reliability requirements. Currently seeking a more code-heavy role after moving into a more advisory position.”

“Full-stack TypeScript engineer with hands-on experience building e-commerce and subscription/dashboard features across React, Node.js/Express, MongoDB, and PostgreSQL. Has owned features through AWS/GitHub Actions deployment and post-production support, including diagnosing stale-cache issues in production and improving team velocity by standardizing reusable UI components.”

“Full-stack engineer with hands-on experience building enterprise workflow management platforms across React/TypeScript, Node.js/Express, Angular, and .NET Core microservices. They stand out for owning features through production, solving real-world data consistency and legacy-data issues, and driving architectural and SQL performance improvements that made dashboards faster and more reliable.”

“Full Stack Engineer with hands-on experience owning customer-facing products end-to-end, emphasizing fast iteration via feature flags and risk-based testing for critical user flows. Built TypeScript/React systems with shared types and clean backend layering, and has microservices experience using RabbitMQ to decouple services and manage scale issues like queue backlogs. Also created an internal dashboard for dev/QA to centralize build/test/deploy visibility and iterated on it through lightweight user research and usage metrics.”

“Full-stack engineer who owned end-to-end delivery of a customer-facing financial services web platform and built internal tooling for engineering teams. Strong in microservices and event-driven systems (Kafka/RabbitMQ), distributed transaction management (saga), and production performance/observability—achieving ~40% backend response-time improvement through database and query optimization.”

“Built and productionized an AI NL-to-SQL capability inside legacy accounts receivable software (React + Spring Boot + Postgres/pgvector RAG), adding semantic caching and a SELECT-only validation layer to satisfy infosec. Achieved measurable impact (3 days to seconds turnaround, 60% token cost reduction, 50% latency reduction) with strong adoption (40 analysts, 50+ queries/week) and documented/monitored via Confluence + logging and user feedback loops.”

“Cloud/DevOps-focused engineer with production experience in Linux, AWS, Kubernetes, and cloud-native architectures. Has built GitHub Actions CI/CD pipelines for containerized Kubernetes deployments and implemented Terraform-based AWS infrastructure with modular design and remote state/locking (S3 + DynamoDB) plus PR/CI-driven change control.”

“Full-stack engineer with experience at Capital One and Prime Softech owning production systems end-to-end: secure authentication (Java/Spring Security + React/Redux) through AWS ECS deployments with Terraform and CI/CD. Strong reliability/observability focus (Prometheus/Grafana/ELK/CloudWatch) with quantified improvements (15% reliability gain, 30% fewer post-release defects). Also led legacy monolith-to-microservices refactors and built real-time Kafka/Spark ingestion pipelines for analytics/fraud detection.”

“Data engineer focused on sales/marketing analytics pipelines, owning ingestion from CRMs/ad platforms through warehouse serving and dashboards at ~hundreds of thousands of records/day. Built reliability-focused systems including dbt/SQL/Python data quality gates with alerting, a resilient web-scraping pipeline (retries/backoff, anti-bot tactics, schema-change detection, backfills), and a versioned internal REST API with caching and strong developer usability.”

Vansh Amara

Screened

Junior Software Engineer specializing in AI systems and robotics infrastructure

Madison, WI1y exp

“Robotics software engineer with hands-on ROS 2 experience building real-time perception/control infrastructure and multi-sensor fusion (radar/ultrasonic + GNSS/IMU) with deterministic latency and safety fallbacks. Debugged rover navigation drift via rosbag replay and timing analysis, improving state estimation by gating GNSS and switching to SLAM when GPS degraded. Also brings strong distributed-systems and build/CI tooling experience (gRPC/Protobuf, Docker, Bazel cross-compilation for ARM/RISC-V, GitHub Actions).”

Sanjana Kirthi

Screened

Junior Software Engineer specializing in backend platforms and cloud-native systems

USA3y exp

“Backend engineer from Emphasis who modernized legacy, tightly coupled workflow systems into observable, event-driven microservices using Kafka. Led a monolith-to-microservices refactor with shadow traffic, feature flags, canary rollout, dual writes, and reconciliation, and strengthened reliability with idempotent consumers, DLQ/replay, and an outbox pattern to prevent DB/event inconsistency. Strong focus on secure multi-tenant APIs (OIDC/JWT, RBAC/ABAC, Supabase-style RLS) and frontend enablement via OpenAPI and typed client generation.”

Adaya Head

Screened

Mid-level Software Engineer specializing in game development and web/mobile apps

Remote4y exp

“Gameplay engineer who also contributes to game design, currently building a motion-based horror game with educational riddle mechanics (animal/sea-creature learning via in-room info tablets). Has shipped/implemented stealth gameplay systems including power-ups (notably an invisibility mechanic) and iterated features through internal cross-discipline playtests, documentation, and Figma-driven inventory system alignment.”

Praveen LAKSHMAN

Screened

Mid-level Software Engineer specializing in backend systems and workflow automation

Birmingham, AL4y exp

“Early-career AI engineer currently pursuing a Master's, with hands-on experience building and improving RAG pipelines using LangChain. They stand out for moving beyond naive retrieval into multi-step retrieval and feedback-loop designs to reduce hallucinations, and are now exploring multi-agent systems with distinct retrieval, coding, and validation roles.”

“Software engineer who recently shipped an authentication and role-based access feature for a web app, using AI selectively for boilerplate, debugging, and test suggestions while retaining ownership of architecture, security, testing, and final review. Stands out for a disciplined, security-first approach to AI-assisted development and a pragmatic preference for lightweight API-driven solutions over unnecessary framework complexity.”

“Currently serving as VP of Technology since January 2025, this candidate was brought in to build a fintech lending platform from the ground up, including hiring a global team and delivering a unified AI-enabled platform. They combine executive-level ownership with hands-on architecture work, including a customer-facing document agent and Plaid integration, and emphasize pragmatic AI adoption tied to measurable engineering productivity.”

“Backend engineer who optimized an AI-driven portfolio analytics/insights platform at Fidelity, addressing latency and traffic growth by moving services toward microservices, improving service communication, and tuning API/DB performance. Experienced scaling Python/FastAPI services with Docker + Kubernetes autoscaling, and strengthening security/privacy for sensitive client portfolio data used in LLM-based reporting.”

“Built and deployed a production LLM-powered workflow assistant that automated internal marketing/production business tasks (document summarization, repeated Q&A, status updates). Demonstrates end-to-end applied LLM engineering: modular RAG architecture, hallucination/latency mitigation, automated evals to prevent prompt regressions, and Azure-based orchestration (Functions/Logic Apps) with monitoring and controlled rollouts.”

“Software engineer/product owner experience at UnitedHealth Group owning a high-volume claims eligibility console end-to-end (React/TypeScript + Spring Boot microservices) processing 1M+ transactions/day. Strong in event-driven architecture (Kafka/RabbitMQ), HIPAA-aligned security (OAuth/JWT/RBAC), and building internal observability tools that improve incident triage and production reliability.”

“Full-stack engineer with financial services experience (Lincoln Financial) who owned a customer-facing financial portal end-to-end using TypeScript/React and Node/Express. Has hands-on microservices and RabbitMQ event-driven workflows, addressing scale issues like retries/duplicates with idempotency and traceable logging, and built an internal real-time ops/support dashboard to improve monitoring and incident response.”

“Backend/DevOps-leaning engineer with trading/financial systems experience (AIG), focused on reliability: built Python automated test suites to ~95% coverage and integrated them into CI/CD. Has hands-on Kubernetes microservices deployment with GitOps (ArgoCD), plus experience supporting cloud-to-on-prem migrations and building real-time streaming pipelines resilient to spikes and data loss.”

“Built and productionized an LLM-powered support/knowledge pipeline using embeddings and retrieval (RAG) to deliver more grounded, higher-quality responses while reducing manual effort. Focused on real-world reliability and performance—adding structured validation/guardrails, optimizing vector search and context size for latency/scale, and monitoring failure patterns in production. Experienced with orchestration via LangChain for LLM workflows and Airflow for production data/ML pipelines, and iterates closely with operations stakeholders through demos and feedback.”