Vetted API Testing Professionals

“Backend/event-driven systems engineer who built an end-to-end “software robot” for AI-driven invoice processing: FastAPI ingestion + OCR integration + classification mapping, with strong emphasis on reliability (idempotency, retries) and scalability (background workers, event-driven architecture). Experienced in production-grade distributed systems tooling (Kafka, Docker/Kubernetes, GitHub Actions, ArgoCD) and real-time debugging via tracing/telemetry, and expects $10k–$12k/month.”

“Engineering leader from Blackline who has repeatedly rescued and delivered high-visibility products by resetting roadmaps, tightening execution (better specs/estimation), and accelerating team velocity. Scaled a distributed org from ~20 to ~40 engineers by building a new India team with strong hiring rubrics and governance-as-code/SDLC consistency. Also modernized legacy systems into microservices (Kafka/Kubernetes/Apigee) and drove hackathon-to-production innovation using Google Vertex AI.”

“QA automation engineer with ad-tech domain experience (Prebid.js wrapper-based services) who built an end-to-end Python automation framework using Playwright to validate wrapper settings, auction request/response, and analytics payloads. Uses Jenkins-driven CI reporting and feature-categorized regression runs to quickly isolate revenue-impacting defects and coordinate fast fixes with developers.”

“SDE who worked on an MGICS Lab robotics project building a multi-agent model to help agents understand tasks and generate robot instructions, emphasizing task-splitting, checking, and a reflection agent to improve accuracy. Also has experience using GitHub with automated CI/CD pipelines.”

“At Triple Whale, partnered with product, engineering, and sales to bring enterprise LLM-based budget recommendation agents from impressive prototypes to trusted production workflows. Strong in prompt/input tuning, explainable structured outputs, and running tightly-scoped POCs with clear success criteria—plus hands-on technical demos and post-sale implementation to drive adoption.”

“ML/NLP engineer currently working in NYC on a system that connects complex unstructured data sources to deliver personalized insights, using embeddings + vector DB retrieval and a RAG architecture (LangChain, Pinecone/OpenSearch). Strong focus on production constraints—especially low-latency retrieval—using FAISS/ANN, PCA, index partitioning, and Redis caching, plus PEFT fine-tuning (LoRA/QLoRA) and KPI/SLA-driven promotion to production.”

“Early-career developer whose experience comes from classroom projects but has completed full end-to-end web app delivery: implemented login/search/favorites, integrated external APIs, and deployed to Google Cloud for multi-device use. Demonstrates user-centered iteration by recruiting friends to test and provide feedback, and has hands-on production-style debugging experience (e.g., resolving CORS issues during deployment).”

“Backend engineer who has led major platform evolution to cloud-native microservices (Spring Boot on AWS with Terraform) and built scalable, secure FastAPI APIs. Demonstrates strong production rigor with metric-driven validation, canary/phased rollouts, and incremental migrations using shadow traffic/feature flags/parallel writes—achieving faster deployments, fewer incidents, and zero-downtime traffic spikes and migrations.”