Vetted Regression Testing Professionals

“Built and owned an end-to-end AV operations automation and dashboarding platform for USC event operations, used daily to coordinate hundreds of live events. Delivered a React/TypeScript full-stack system integrating Smartsheet APIs with strong reliability practices (typed contracts, validation/fallbacks, safe rollouts) and experience with queue-based microservice patterns (idempotency, retries, DLQs, monitoring).”

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.”

“Deloitte technical implementation lead who functioned like a pre-sales/solutions engineer for ABBYY's intelligent document processing within the Argus GenAI platform. They supported enterprise-scale rollouts across 10+ countries, tailored deployments for local market needs, and combined integration, compliance, and Python automation work to deliver 95%+ extraction accuracy.”

“AI/full-stack engineer who has built both a real-time crypto sentiment platform from scratch and production enterprise RAG search systems at Kore.ai. Stands out for combining strong systems engineering with practical LLM evaluation, retrieval tuning, and careful human-in-the-loop design for high-risk network automation use cases with Cisco.”

“Frontend engineer with experience spanning Amazon Seller Central, Shoptaki, and TCS, focused on turning complex, dynamic workflows into scalable browser-based systems. Particularly strong in schema-driven and metadata-driven UI architecture, including AI-powered analytics interfaces and compliance platforms where adaptability, consistency, and trust are critical.”

“Built and owned Prism, a real-time collaborative coding platform, making key architectural choices around deterministic event ordering and a backend source-of-truth to improve trust under concurrent edits. Also created a Python-based bug analysis and test automation suite that became part of standard engineering workflow, cutting debugging time by ~95% while improving fault detection coverage.”

“AI/ML engineer with HP experience building and productionizing an LLM-powered document intelligence platform (LangChain + Pinecone) to deliver semantic search and contextual Q&A across millions of enterprise support documents. Demonstrates strong MLOps and scaling expertise (Airflow, Kubernetes autoscaling, Triton GPU inference, monitoring with Prometheus/W&B) plus a structured approach to evaluation (A/B tests, shadow deployments, failover) and effective collaboration with non-technical stakeholders.”

“Engineering leader (Credit Karma/fintech) who built internal developer-platform frameworks at near open-source scale, including a unified key management system migrating ~450 services from on-prem HSM to a centralized KMS. Known for driving large cross-team migrations with strong safety mechanisms (canaries, shadow reads, rollback toggles) and measurable DX/ops improvements (60% fewer provisioning requests; 40% faster time-to-first-secret).”

“Backend/platform engineer from Fanatics sportsbook core team with deep experience in real-time ingestion systems (Kafka) and high-throughput performance optimization. Delivered an 87% latency reduction on a Java API handling hundreds of thousands of updates per second, and improved reliability of shared internal libraries via deterministic recovery logic, strong testing, and feature-flagged rollouts.”

“Robotics/ADAS engineer who built an assistive feeding robot with reliable 3D mouth tracking (RealSense + MediaPipe) and ROS 2 integration to a WidowX250s arm, solving depth-noise, timing, and workspace/singularity issues for stable low-latency behavior. Also optimized a real-time lane-keeping controller at Hyundai using signal logging/replay, filtering (LPF/Kalman), and feedforward+PI tuning, with experience across SIL/HIL and CAN-based ECU integration.”

“QA tester with hands-on experience supporting Duolingo’s large-scale, high-stakes releases across iOS, Android, and web. Owns test planning, manual + mobile automation testing, regression, and release verification, with a strong focus on real-world edge cases (low-end devices, poor connectivity, localization/RTL) and rigorous bug triage using JIRA and external user reports.”

“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.”

“Uber engineer who has owned internal products end-to-end across backend (Spring Boot microservices, MySQL) and frontend (React), including performance optimization and secure JWT-based auth. Also shipped a production internal RAG/embeddings LLM support assistant over policy docs and support tickets, with guardrails (confidence thresholds, human review) and an evaluation loop that directly reduced hallucinations.”

Allan Farinas

Screened

Senior Full-Stack Software Engineer specializing in Python and AWS

West Covina, CA11y exp

“Backend/data engineer who has built production Python microservices (FastAPI) and AWS-native platforms for event ingestion and analytics, combining ECS/Fargate + Lambda with CloudFormation-driven environments and strong secrets/IAM practices. Experienced modernizing legacy logic with parallel-run parity validation and safe phased cutovers, and has demonstrated measurable SQL tuning wins (20–30s down to 1–2s) plus incident ownership in Glue/Step Functions ETL pipelines.”

John Hoffman

Screened

Senior Data Engineer specializing in Databricks, Spark, and AWS for government healthcare data systems

Windsor Mill, MD12y exp

“Python/AWS engineer focused on batch-processing and data workflows, including building reusable S3/boto3 utilities with reliability features and IAM-based auth. Has led low-risk legacy modernizations using parity testing plus a month of parallel production runs, and has owned production issues end-to-end (including fixing a client-side Excel macro) while contributing to significant AWS cost reductions (~$10k/month).”

Samatha Amsala

Screened

Mid-level Data Engineer specializing in cloud data warehousing and analytics

Omaha, NE6y exp

“Data engineer at American Express who owned end-to-end pipelines for transaction and customer data used in finance reporting and risk analytics, processing ~5–8M records/day. Built Airflow-orchestrated ingestion (including external APIs/web sources) with strong data quality controls, monitoring/alerts, and resilient backfill/retry patterns, and also shipped a versioned REST API serving aggregated metrics to analytics teams.”

“Frontend-focused product engineer from TrialTrace who owned features end-to-end across product decisions, architecture, implementation, and testing. Strong in TypeScript/React applications with complex data visualization and dashboarding, including refactoring core coordinate logic, building filter-state architecture, and shipping fast user-driven features.”

“Built and deployed a production LLM/RAG chatbot at Wells Fargo for securely querying regulated financial and compliance documents, emphasizing low hallucination rates, explainability, and strict governance. Experienced with LangChain multi-agent orchestration plus Airflow/Prefect pipelines for ingestion, embeddings, evaluation, and retraining, and partnered closely with compliance/operations to drive adoption through demos and feedback-driven retrieval rules.”

“Founder/builder of an EdTech startup (robograde.io) who personally conducted on-site classroom discovery with teachers and rapidly iterated the product based on real-world feedback. Implemented a Canvas LMS integration and refined it through weeks of in-person testing, and handled a live production grading failure by quickly debugging and deploying a fix, then adding fault-tolerant/backup API design.”

“Backend/Full-stack engineer who built a Go-based API for a real-time eye-tracking system (calibration/recording/streaming) and debugged intermittent long-session timeouts through improved observability and concurrency refactors. Also shipped an LLM-driven "Doctor Simulator" product end-to-end (React/Node/Go/MongoDB/OpenAI), including structured prompts, deterministic verification/termination logic, and production guardrails like validation, retries, and prompt versioning.”

“QA professional with Apple experience supporting the macOS Sonoma release, owning daily monitoring of submissions, crashes, regressions, and release verification across multiple OS/device builds. Notably isolated a memory-related issue in the Safari suite that caused an 18-hour build backlog and 156+ test crashes, leading to a Python-script fix that restored build times to ~1 hour and helped keep the release on schedule.”

“QA/automation engineer with experience at Riot Games’ player platform, owning E2E automation for mission-critical authentication/account flows using Playwright/JavaScript plus API automation. Built CI merge gates and nightly verification with Slack reporting, and repeatedly caught backend-driven session/authorization regressions before production. Known for stabilizing flaky UI tests via selector strategy and network intercepts, and for influencing design early with testability hooks and telemetry.”

Manasa Mangipudi

Screened

Mid-level Machine Learning Engineer specializing in NLP and computer vision

3y exp

“AI/ML engineer with production experience building an LLM-powered resume-to-job matching and feedback product using RAG, with a strong focus on latency, hallucination control, and scalable deployment. Experienced orchestrating ML inference and backend services on Kubernetes and applying rigorous evaluation/guardrail practices; also partnered with business/product stakeholders at Walmart to improve an NLP-based supplier support system.”

Akshaya Chiduruppa

Screened

Mid-level Quality Assurance Engineer specializing in AI/ML and Apple ecosystem testing

Seattle, WA4y exp

“QA automation engineer with end-to-end ownership of a regression suite for a warehouse loan management platform (.NET/Angular), using Selenium (Java/Cucumber/POM) and Cypress. Improved suite stability and expanded risk-based coverage (DB/API/SQL, RBAC approval workflows), catching critical financial defects like EMI calculation errors and cutting regression effort by ~50% while gating releases via GitLab CI/CD with actionable Slack reporting.”