Vetted End-to-End Testing Professionals

“Amazon Alexa engineer who architected and shipped a GenAI Knowledge Agent used by 2M+ customers, focused on making LLM outputs auditable via citations and a verification layer that prevents hallucinations. Built the full vertical slice (FastAPI/LangChain backend + React/TypeScript streaming UI) while keeping p99 latency under 200ms, and has proven incident response experience on AWS (Lambda/DynamoDB scaling issues).”

Lawrence Cheng

Screened

Mid-Level Backend Software Engineer specializing in FinTech platforms

San Francisco Bay Area, CA6y exp

“Backend/platform-focused engineer who builds scalable onboarding and data ingestion pipelines for complex client data formats, emphasizing staged validation, idempotent job boundaries, and safe rollouts behind feature flags. Strong in production diagnostics (Kibana/Logstash, SQL, debugger traces) with a concrete example of finding a regression causing incorrect Tax Loss Harvesting alert counts within a day, and experienced enabling both engineers and customer-facing teams through docs, runbooks, and technical walkthroughs.”

Jeremiah Medina

Screened

Senior AI/ML Engineer specializing in LLMs, RAG, and cloud-native MLOps

Orlando, FL11y exp

“Built and owned a real-time clinical AI assistant at Andor Health, taking it from prototype through deployment, monitoring, and iterative improvement. Brings strong healthcare-focused GenAI experience across RAG, hybrid retrieval, LoRA fine-tuning, and production Python services, with measurable gains in accuracy, speed, and reliability.”

“Early-career software engineer who owns revenue-critical invoice processing and internal ops tooling end-to-end. Has built TypeScript/React systems backed by MongoDB and Temporal, and designed scalable SQS-based onboarding workflows with FIFO/DLQ monitoring. Notably redesigned an Authzed SpiceDB authorization model, shrinking a 500+ line schema to ~20 lines while meeting sub-100ms p95 latency.”

“ML/LLM engineer with Stripe and Adobe experience who productionized a transformer-based Payments Foundation Model for real-time fraud detection at global scale (billions of transactions). Built petabyte-scale ETL/feature pipelines (Spark/EMR, Airflow, dbt, Kafka/Flink) and achieved <100ms multi-region inference (EKS, TorchServe, edge/Lambda, GPU/CPU routing) with strong PCI-DSS/GDPR compliance and explainability (SHAP/LIME), reporting a 64% fraud accuracy improvement.”

Shahmeer Malik

Screened

Junior Software Development Engineer specializing in cloud security and CI/CD

Herndon, VA2y exp

“Backend/security-focused engineer supporting a service with 100k+ monthly users. Built an automated load-testing suite that reproduced and mitigated catastrophic host failures from oversized SCP/rsync transfers via host-level throttling, and proposed a future sharding approach for very large transfers. Also created an internal agent to summarize anomalous metrics and provide ready-to-run debug queries, significantly reducing ops review time.”

“Built and owned the end-to-end architecture for a Quick Flows “research card” backend at AWS, using an event-driven AWS stack (SNS/SQS, DynamoDB, S3) to support asynchronous research output processing and status tracking. Emphasized maintainability via unit tests, smoke tests, and CI/CD with staged environments (devtest and gamma).”