Vetted Regression Testing Professionals

“Robotics software engineer who owned the end-to-end navigation stack for a mobile manipulation robot (Cone-E), integrating ZED-2i SLAM into a real-time occupancy grid with live obstacle avoidance, A* planning, and lookahead control. Strong in real-time debugging and stability improvements (goal snapping/locking, obstacle persistence, rate-limited replanning) and validates changes on hardware, supported by simulation (Gazebo/Webots) and Docker/CI-based testing.”

“LLM/RAG practitioner who productionized an LLM-driven customer communication and transaction understanding system at PayPal, emphasizing privacy/compliance guardrails and large-scale data normalization. Experienced in real-time debugging of hallucinations via retrieval pipeline tuning and in leading hands-on developer workshops and sales-aligned POCs to drive adoption.”

“Backend/automation engineer who led the design of an OOP Python test automation framework for AWS infrastructure (Behave + Jenkins), cutting regression effort from weeks to a 3–4 hour run. Has hands-on cloud and DevOps experience across AWS (boto3, ECS, AMI automation via GitHub Actions) plus data/migration work including on-prem-to-cloud Oracle Retail DB migration with rollback planning and a Kafka + ML fraud-detection streaming pipeline.”

“QA tester with hands-on experience across web, mobile, and API testing, including requirements gathering, test planning/case creation, and executing system/regression/UAT. While new to console game testing and platform certification checklists (TRC/XR/LOT), they emphasize strong testing fundamentals, API automation experience, and using AI tools to ramp up quickly.”

“Full-stack engineer with strong DevOps/AWS production experience who builds and operates multi-agent AI systems end-to-end (Streamlit/Python through Docker/Kubernetes and ECS/Fargate). Has delivered measurable outcomes: sub-2s latency and ~92% routing accuracy for an AI wellness assistant, shipped an AI-for-BI prototype in under 6 weeks cutting analysis time ~40%, and improved pipeline iteration speed ~35% via modularization and CI/regression checks.”

“Game QA professional with live production experience owning QA strategy for a cross-platform seasonal loadout system in a live server shooter. Works in Agile/Scrum with CI/CD, using Jira + TestRail (including two-way sync) to drive traceable test coverage and fast triage via evidence-rich bug reports. Emphasizes risk-based coverage, regression discipline across builds, and converting gameplay feel into actionable design/engineering feedback.”

“Software engineer with hands-on experience building a distributed ticketing system on AWS (Terraform, Go, MySQL) focused on high-concurrency reliability (locks/queues to prevent duplicate ticket confirmations) and load-tested performance. Also independently owned and shipped an Airflow automation script to stop/restart workflows during deployments with email notifications, reducing manual operational effort.”

“Full-stack engineer with fintech/trading domain experience (Fidelity) and startup SaaS CRM/billing platform work (Zoho), building real-time portfolio analytics and trade-processing systems. Strong in microservices, event-driven architectures (Kafka/WebSockets), and AWS/Kubernetes operations with measurable performance gains (~34–35% latency reduction) and maintainability improvements (~40% faster deployments). Targeting a founding full-stack engineer role in NYC with meaningful equity.”

“Game industry QA tester with several years of experience supporting multiple AAA titles, including multiplayer ownership and work spanning pre-alpha through gold master and post-launch updates. Known for proactive edge-case exploration—e.g., finding and documenting a late-stage crash tied to a mission timer interaction—backed by strong evidence capture (video, crash dumps) and thorough verification/regression practices.”

“Gameplay QA professional with hands-on experience testing and iterating on live production changes for 2XKO, including move/frame adjustments and system interactions. Known for structured ISTQB-based test planning, video-backed documentation, and strong defect isolation (e.g., tracing knockdown roll issues to collision capsule sizing) to speed up developer triage and resolution.”

“Built and productionized a secure internal RAG-based AI assistant (LangChain/FastAPI/FAISS on GCP), tackling real-world issues like latency, retrieval speed, and hallucinations—delivering 25% faster retrieval and 99.9% uptime. Also implemented scalable, reliable ML retraining orchestration with AWS Step Functions/SageMaker/Lambda and partners closely with compliance analysts to iteratively refine prompts and outputs to meet governance standards.”