Vetted Unit Testing Professionals

“Full-stack engineer at an early-stage EdTech startup building an AI-tutoring product; owns most of a Django REST backend, CI/CD, and key customer-facing features like FERPA-compliant auth, subscription payments, and real-time LaTeX input/rendering. Also built a /rPlace-style real-time multiplayer canvas (PolyPlace) using microservices, WebSockets, and event sourcing, with performance-focused client rendering (zoom/pan/viewport-based updates) and stress testing.”

“Full-stack/product-leaning engineer in logistics and high-traffic portals who ships production AI features: built an AI-assisted shipment status Q&A system using Pinecone + GPT-4 and a high-volume Python ingestion pipeline (500K+ records/day), delivering 35% fewer support tickets and cutting resolution time from 11 to 4 minutes. Also led a legacy Angular-to-React/TypeScript rebuild that boosted Lighthouse performance from 60 to 90, and has hands-on AWS EKS operations experience including resolving a 3x traffic scaling incident.”

“Full-stack engineer who has delivered production customer analytics/dashboard features using Next.js App Router + TypeScript on the frontend and Java Spring Boot microservices on the backend. Demonstrates strong production ownership (monitoring latency/error rates/adoption) plus hands-on performance work across React rendering and Postgres query/index optimization, and has implemented Temporal-like durable workflows with retries and idempotency.”

“Customer-facing software engineer who builds and deploys practical AI/RAG solutions (e.g., an AI assistant for searching billing PDFs) by deeply understanding support workflows and iterating with users. Demonstrates strong production instincts—quickly stabilizing peak-traffic API timeouts with caching/background jobs, then implementing durable fixes with proper monitoring and maintainable code practices.”

“Senior frontend developer with end-to-end ownership of modernizing a legacy Laravel/PHP product into a Next.js 14 + React + TypeScript stack, using TurboRepo for incremental integration. Emphasizes quality and scale through unit testing, Datadog monitoring, and performance-focused UI work (dashboards with charts/usage analytics, minimizing re-renders).”

“Data scientist/researcher who has built two multimodal LLM systems: an AI-assisted medical triage pipeline using GPT-4o vision + RAG with confidence-scored red/yellow/green outputs, and a master’s project on multimodal cyberthreat detection combining multiple models and using TinyLlama to generate human-readable risk reports. Also partnered with business analysts at Sanvar Technologies to deliver a churn prediction pipeline and Tableau dashboard for decision-making.”

“Unity game developer with a standout gameplay-design contribution: proposed and implemented an early merge-to-upgrade mechanic (halving unit count to increase strength) that became foundational to a successful merge battle/merge dragons-style game. Has multiplayer/VR mod experience and is currently learning Unity Netcode for GameObjects, with confidence switching to Photon Fusion. Also applies AI workflows for maintainable coding and rapid mobile icon/banner prototyping to support A/B testing and CPI optimization.”

“Frontend engineer experienced leading enterprise-grade analytics dashboard and portal work by embedding and extending Apache Superset within a client-facing platform. Emphasizes scalable plugin-driven React/TypeScript architecture, quality-at-scale (TypeScript + Jest + reviews), and safe, fast-paced delivery using feature flags, staging validation with real datasets, and performance optimizations like code splitting and lazy loading.”

“Frontend-focused builder who worked on the VITALES.LIFE healthcare app using Next.js/React Native alongside multiple backend technologies (NestJS, Go, Python/FastAPI) on Firebase/GCP. Has experience delivering client-driven MVPs (e.g., Omnicommander, Talentus) and uses Jest for test coverage while emphasizing code reuse and non-duplicative components.”

“LLM engineer/data analyst who built a production RAG QA assistant over the Jurafsky & Martin NLP textbook to reduce hallucinations and provide explainable, source-grounded answers. Experienced with LangChain/LangGraph orchestration, retrieval optimization (embeddings, vector DBs, caching), and rigorous evaluation/monitoring (Retrieval@K, A/B tests, telemetry/drift). Previously communicated analytics insights to non-technical stakeholders at GS Analytics using Power BI and simplified reporting.”

“Frontend engineer who has led customer-facing React + TypeScript products end-to-end, building complex dashboards with robust async state patterns (caching, deduping, cancellation, optimistic updates) and strong quality practices (TypeScript standards, layered testing, production monitoring). Experienced modernizing inherited codebases through modularization and performance work (code splitting/memoization) while aligning stakeholders and shipping safely via feature flags and staged rollouts.”

“Frontend engineer with ~6 years of experience delivering SEO- and performance-sensitive web apps (e.g., an automobile sales platform built with Next.js SSR) and complex React+TypeScript dashboards for energy management/heat pump scheduling. Has handled real-time data challenges by integrating MQTT, and combines hands-on frontend ownership with Agile team coordination (standups, task assignment, client demos, requirements).”

“Frontend engineer who led end-to-end delivery of a financial data grid and optimized it to handle millions of rows using batching and progressive rendering. Experienced modernizing legacy Razor UIs into maintainable React + TypeScript implementations, leveraging React Query and Jotai, and shipping via incremental builds and feature toggles with close QA/client collaboration.”

“Forward Deployed Engineer at EasyBee AI who productionized a self-storage customer’s multi-agent LLM system end-to-end—rebuilding it with LangGraph/CrewAI, integrating with real property management + CRM systems via an MCP server, and adding observability/guardrails for reliable daily use. Experienced in live troubleshooting of agentic workflows, developer demos/workshops (including an open-source project, MerryQuery), and partnering with sales to close deals through customer-specific technical demos and fast integration feedback loops.”

“Internship at Discovery Education building a production LLM/RAG chatbot that let marketing and sales teams query and interpret Looker/BI dashboards in natural language, with responses grounded in compliance and state education standards. Emphasizes rigorous evaluation (faithfulness/precision/recall/latency) plus user-feedback analytics, and used LangChain for orchestration, chunking/context-window control, and integration with enterprise sources like SharePoint.”

“Full-stack engineer from Clairvoyant who led end-to-end delivery of a cloud-native, event-driven platform: Spring Boot microservices + Kafka real-time streams with an Angular UI, migrated and containerized on AWS, and automated CI/CD with Jenkins/Maven/Git. Demonstrates depth in distributed consistency challenges (partitioning, consumer lag/duplicates) and database performance tuning across SQL/NoSQL under heavy workloads.”

“Software/automation QA professional with hands-on Oculus VR testing at Telkom, covering controller inputs, tracking reliability, performance/FPS stability, thermal behavior, crash reproduction, and system-level events (standby/resume, low battery, network interruptions, guardian changes). Familiar with the intent and coverage areas of console certification frameworks (Sony TRC/Microsoft XR/Nintendo LOTcheck) and uses AI to speed up log analysis and test case creation.”

“Full-stack engineer with fintech payments experience who shipped an end-to-end guest invoice payment flow emphasizing reliability under retries/failures (idempotency via DynamoDB, async processing with Lambda/EventBridge/SQS + DLQ). Also built a FastAPI backend with Cognito/JWT + scoped guest tokens and a polished React/TypeScript checkout UX, and has performance-focused Postgres/Redis design experience for flash-sale e-commerce workloads.”

“Startup-style full-stack/backend engineer with hands-on AWS architecture experience who shipped an LLM-driven assessment-question automation feature (Python microservice calling AWS Bedrock via SQS, deployed on Lambda) with strong validation/guardrails and retry strategies. Also improved production scalability by moving a CPU/IO-heavy file upload path out of a Go API into a queue/Lambda design monitored with CloudWatch, and has React+TypeScript experience optimizing analytics dashboards.”

“Full-stack engineer operating in early-stage, high-velocity environments (OpGov.AI/UST Calibrate) who ships production Next.js App Router features end-to-end (RSC, Server Actions, SEO, RBAC, caching) and owns performance post-launch. Demonstrates strong data/infra depth—designed Postgres JSONB-based event models for DevOps/DORA analytics and tuned queries from ~2s to <50ms, plus built durable ingestion workflows with retries and idempotency on Azure.”

“Software QA professional with 10+ years of experience across e-commerce, medical applications, and database management systems, often serving as the sole QA on projects. Has implemented QA processes from the ground up (bug workflow and release checklists) and emphasizes disciplined, highly readable ticketing and traceability-driven test maintenance; no professional game studio testing experience.”

“Backend/AI engineer who has built production LLM orchestration and agentic workflow systems in Python/FastAPI on Kubernetes across AWS/Azure. Demonstrated strong reliability engineering by debugging a real-world memory retention issue that caused latency spikes/timeouts, and strong data/performance chops with a PostgreSQL optimization that cut query latency from ~1.2s to ~15ms. Targets roles building scalable, guardrailed AI-driven workflow automation with robust observability and human-in-the-loop controls.”

“Built and shipped a production multi-agent LLM system at Solena that automated internal project intake, validation, reporting, and stakeholder communications using Python, SQL, and LangChain, with strong emphasis on reliability (structured validation, safe defaults, logging, and state tracking). Also used LangGraph to orchestrate a multi-step video summarization pipeline, and has experience partnering with non-technical stakeholders to define “completion” criteria and reporting needs.”

“Full-stack engineer who has shipped and operated generative-AI chat/QA features end-to-end, including a RAG-based pipeline with guardrails and cost/latency monitoring in production. Experienced with React/TypeScript + Node/Postgres architectures, Dockerized deployments to AWS (EC2) via GitHub Actions CI/CD, and building reliable ingestion/ETL systems with idempotency, backfills, and reconciliation.”