Vetted Test-Driven Development Professionals

“Backend/platform engineer who built an LLM-driven QA automation system (“mockmouse”) using a Flask orchestration microservice, Socket.IO real-time updates, Redis caching, and strict Pydantic schemas to turn prompts into reliable action graphs and automated browser tests. Has hands-on Kubernetes delivery experience (Docker/Helm/Jenkins) and has supported large migration programs, validating ETL cutovers with 1M+ synthetic records and rigorous output comparisons; also built event-driven monitoring/anomaly detection streaming into Grafana.”

“Systems-focused C++ engineer who built a 32-bit CPU simulator end-to-end (custom ISA, full memory model, fetch-decode-execute loop) and solved tricky recursion/stack-frame correctness issues through heavy instrumentation and tracing. Has strong Linux and user-kernel boundary experience (procfs) plus modern build/test tooling (Docker, CI/CD, pytest), and is confident ramping quickly into ROS/ROS2 despite not having used it directly.”

“Machine learning lab assistant at Eastern Illinois University who productionized a voice-enabled conversational AI system: redesigned it with RAG, LoRA fine-tuning (including text-to-SQL), and safety guardrails, then deployed a scalable API supporting ~1,000 daily queries. Also partnered with customer-facing teams during a BlueFi internship by building demos/APIs and accelerating releases via Terraform + AWS CI/CD automation.”

“Backend/data engineer with healthcare/medical-device experience who scaled a HIPAA-constrained local data platform to 50k users and 1B+ records, boosting processing from <500 to ~50k datapoints/sec using sharding, indexing, and SQL over Parquet (DuckDB). Strong security and reliability focus (JWT/RLS, least privilege, heavy unit/E2E testing) and a TypeScript specialist who uses type design to eliminate edge-case failures.”

“Backend engineer who built and scaled a FastAPI-based backend for an AI-driven maintenance system automating vendor sourcing/bidding/communication. Emphasizes async, message-driven architecture with strong observability and state-machine-driven workflows, plus robust webhook/idempotency patterns to prevent duplicate/out-of-order events from causing bad bids or state changes.”