Vetted Automated Testing Professionals

Kingsley Torlowei

Screened

Senior Software Engineer specializing in AI systems and data platforms

Remote8y exp

“Built and productionized LLM agents that ingest multi-source workplace data (Slack, meetings, calendars, PM tools) to extract entities (tasks/decisions/risks/initiatives) and generate customer insights like risk alerts, deadline-miss prediction with evidence, and workload overload detection. Also architected a graph-DB-backed multi-step agent using LangChain + Pydantic with async queue/worker execution and LLM-as-judge evaluation plus human review loops.”

Pranav Zagade

Screened

Junior Software Engineer specializing in full-stack and AI systems

Arizona, USA3y exp

“Built and shipped an LLM-powered support agent for Community Dreams Foundation that automated intake and Jira ticket creation using RAG, structured outputs, and strong production guardrails. Demonstrated practical production AI experience with 92% routing accuracy, 98% uptime, and a 31% improvement in first-response accuracy, plus hands-on work in observability, evals, idempotency, and failure handling.”

“Unity/C# engineer with hands-on ownership of a server-backed resource loading pipeline that kept build size small, preserved UI responsiveness via parallel services, and handled dynamic asset replacement with ghost objects and memory cleanup. Also brings a pragmatic, architecture-first approach to AI/LLM integration, emphasizing provider abstraction, testing, cost control, and guardrails for hallucinations.”

“ML engineer with hands-on experience building banking AI systems end-to-end, including a customer-targeting model that improved campaign response rates by about 10%. Also shipped a RAG-based banking FAQ/support feature with safety guardrails and production optimizations around retrieval quality, latency, and cost, plus reusable Python services that reduced duplicate work for other engineers.”

“New-grad backend engineer who built a real-time genome analysis pipeline, replacing a slow batch system with an event-driven distributed architecture in Python/Redis and a React progress dashboard. Reports ~6x improvement and cutting analysis time from days to hours with zero data loss under peak load, emphasizing reliability patterns like retries and idempotency plus API security (JWT/RBAC/HTTPS).”

“DevOps engineer (State Farm) with hands-on ownership of Python backend services and data pipelines, deploying microservices and workers on Kubernetes using GitOps (Argo CD). Has led complex cloud-to-on-prem/hybrid migrations with staged cutovers and rollback planning, and built Kafka-based real-time streaming pipelines with schema governance, autoscaling, and strong observability.”

“Data engineer who has owned production pipelines end-to-end, ingesting 50–100 GB/day from APIs/S3 and near-real-time Kafka into Snowflake with strong data quality gates (Great Expectations/dbt) and Airflow-based reliability (SLAs, alerting, dashboards). Also built a Snowflake-backed REST data API with caching/pagination and versioned endpoints, and designed a compliant, scalable web-scraping system with anti-bot handling and safe backfills.”

Purva Chakravarti

Screened

Senior Full-Stack Software Engineer specializing in scalable web apps, cloud, and blockchain/AI

Chino, California11y exp

“Full-stack engineer with strong production ownership across React/TypeScript, Node.js, and AWS (EC2/ECS/RDS/CloudWatch), including CI/CD, observability, and incident response. Delivered a secure RBAC workflow module end-to-end and achieved measurable gains (~30–40% latency reduction, ~50% error reduction) that lowered infra/ops costs. Comfortable in high-ambiguity startup environments—shipped a payment module within 2 days of joining with no documentation.”

“Software development intern who owned and shipped a production-used WeChat mini-program (JavaScript + MongoDB) serving ~3,000 users in a semester. Emphasizes maintainable UI architecture through modular, reusable components and clear separation between UI presentation and data/business logic, with a performance mindset (caching/reducing redundant updates).”

“Software engineer (Alpine Bank) focused on modernizing high-traffic customer-facing systems with React/TypeScript frontends and Spring Boot microservices. Has hands-on experience stabilizing and scaling event-driven architectures with Kafka (idempotent consumers, partitioning, retry queues) and building internal observability dashboards that materially sped up post-deployment verification and improved release confidence.”

“Co-founder at Skoolive who built a multi-agent LLM application to help users understand complex research papers (including PDF interaction and flowchart-style representations), moving from prototype to production using Gemini SDK and deployment to Runway. Also developed and demoed a web-agent benchmarking framework, running hands-on sessions with customer-facing teams to improve agent reliability and drive adoption.”

“Robotics project manager and software lead for an underwater ROV (MATE 2024–2025), building a ROS 2 Jazzy stack on Raspberry Pi and a serial Pi-to-Arduino thruster control system for a 6-thruster configuration. Also has internship experience creating automated functional test pipelines using Jenkins, Selenium, and Python, plus exposure to Isaac Sim for simulated/synthetic data generation in an embodied AI hackathon.”

“Engineering leader who modernized infrastructure by migrating a ~100-server co-location setup to AWS/GCP with IaC, auto-scaling, and fault-tolerant design, reducing hardware upgrade burden. Also led a key analytics architecture shift from MySQL to ClickHouse to enable highly granular ad revenue attribution and profitability insights, while scaling the dev org from 2–3 to ~12 with stronger CI/testing and review processes.”

“QA automation engineer with hands-on ownership of both UI and API test automation, including building an API test module from scratch to validate all Swagger-exposed endpoints with positive/negative coverage and pairwise optimization. Experienced stabilizing flaky Cypress tests through improved selectors (data-cy) and API-call synchronization, and integrating tiered test suites into GitLab CI with merge/release gates plus JUnit/HTML reporting and Slack notifications.”

Hammad Ur Rahman

Screened

Senior DevOps Engineer specializing in cloud infrastructure and CI/CD

Boston, Massachusetts11y exp

“IBM Power/AIX engineer who has owned a 150+ LPAR AIX 7.x estate with VIOS/HMC/vHMC and PowerHA in production, including real outage and failover recoveries. Also brings modern DevOps/IaC experience—built Jenkins pipelines deploying to AKS and implemented Terraform on AWS with remote state, locking, and drift management.”

Anil Babu Bollina

Screened

Senior Computer Vision Engineer specializing in industrial automation and 2D/3D perception

Nashville, TN8y exp

“Machine-vision engineer who designed an end-to-end inline inspection station for white wood pallets, combining laser line profilers with 2D color line-scan imaging to detect protruding nails (~2mm threshold) at conveyor speeds. Solved real production constraints (lighting reflections, per-trigger depth/color alignment, barcode tracking) and improved system accuracy from ~80% to 99.5% using barcode symbology changes and Keyence reader AI features.”

Berkan Özgür

Screened

Senior XR Engineer specializing in spatial computing and cross-platform Unity systems

San Jose, CA9y exp

“XR/Unity developer who built an underwater experience (Visutate) featuring reactive flocking fish that respond to user presence and hand-feeding interactions. Also implemented multiplayer using Unity Netcode, addressing sync challenges via reduced streamed data and client-side prediction; prefers impactful work in startup-style environments.”

“Candidate is targeting a CTO Venture Studio role and positions themself as a technical partner to founders rather than a founder personally. They demonstrate strong fluency in early-stage startup evaluation, especially around validating whether a product truly tests the business hypothesis and whether the underlying technology can scale significantly.”

“Backend engineer focused on real-time, event-driven systems (Java microservices) handling high-frequency data with low-latency and reliability requirements. Strong in Kafka-based asynchronous architectures, Redis caching, JVM/query tuning, and scalable deployments on Docker/Kubernetes with Jenkins CI/CD; no direct ROS/robotics experience but has closely related distributed communication patterns.”

“Freelance Unity/XR developer with multiple Meta Quest projects (including non-game XR apps) and a 1st-place win at Meta’s Sense AI hackathon in Barcelona for an AI camera-access VR assistant for vehicle repairs. Built a VR Spanish-learning experience solo and has hands-on experience optimizing VR performance (culling, view restriction) and integrating voice recognition for language interactions.”

“Full-stack TypeScript/React/Next.js builder who created an end-to-end customer-facing product (AI Job Master) that generates personalized outreach from resumes and job descriptions. Demonstrates strong product + engineering ownership with rapid MVP iteration, instrumentation-driven prioritization, and pragmatic reliability patterns (microservices, queues, correlation IDs, retries) while tackling a key AI challenge: user trust and output consistency.”

“Backend/infra-focused engineer who owned production systems for distributed ML experimentation (hyperparameter tuning across a cluster with GPU scaling, custom scheduling, and checkpoint-based fault tolerance). Also built and operated a low-latency log validation service using queued async workflows with idempotency, retries/backoff, and strong observability, plus experience building resilient Selenium-based browser automations for complex multi-step web flows.”

“Built and owned a production RAG search/Q&A platform at Data Integrity First for a client with a large, hard-to-search document library, deployed on AWS. Drove major adoption gains by adding source attribution (users trusted answers more) and improved system performance with guardrails, logging, and iterative chunking/OCR normalization—cutting fallback rate from ~22% to under 10%.”