Vetted MySQL Professionals

“Platform-minded JavaScript/TypeScript engineer who has maintained and evolved shared NPM-distributed libraries at Capital One and HCA Healthcare, treating internal packages like open source (issue triage, PR reviews, roadmap, docs). Known for methodical debugging and performance work—e.g., diagnosing latency spikes via load testing/instrumentation and redesigning middleware to avoid redundant parsing—paired with strong developer enablement through examples and migration notes.”

“Small-team builder of Promethium’s “Mantra” next-gen agentic text-to-SQL engine, using vector DB + LangGraph tooling and SQL validation/evaluation to improve query accuracy. Experienced in diagnosing production LLM workflow failures via LangSmith traces and in running hands-on developer workshops and pre-sales POCs with live debugging and real customer data.”

“Maintained and improved a set of JavaScript packages at JPMorgan, including a major refactor of an event-emission layer used in LLM streaming that delivered ~20% runtime speedup with no API changes. Known for a measurement-driven performance approach (profiling + simplification + validation), strong backward-compatibility discipline, and documentation that accelerates internal adoption and reduces support questions.”

“Backend/platform engineer who led an end-to-end Python (FastAPI) transaction analytics microservice for real-time financial monitoring, including SQS ingestion, scoring/aggregation, and low-latency APIs. Strong AWS + Kubernetes/GitOps background (EKS, ArgoCD, Jenkins, ECS/ECR, CloudWatch) with hands-on experience scaling event-driven systems and executing phased on-prem to AWS migrations.”

“Backend engineer who built a containerized Flask service powering an engineering metrics dashboard by syncing GitHub and Jira data into PostgreSQL, with strong emphasis on schema design, query performance, caching, and background processing. Has hands-on experience with SaaS multi-tenancy (tenant scoping + Postgres RLS) and integrating AI/ML inference via separate model-serving services (FastAPI + TensorFlow Serving) and external APIs (OpenAI/Hugging Face/PyTorch).”

“QA tester with experience at Tokopedia (major Indonesian e-commerce) handling concurrent web/Android/iOS releases, including regression testing, stakeholder coordination, and full bug-ticket lifecycle management. Has additional PC/mobile game testing exposure (personal/adhoc) and uses AI tools to generate edge test cases and detect bug patterns; interested in taking on heavy, high-impact projects.”

“Wayfair strategic sourcing/procurement professional who led a major shift from push-based replenishment to a demand-driven pull model, combining SAP IBP/S4HANA planning with supplier renegotiations and performance scorecards. Drove measurable outcomes including $100K annual savings, 98% on-time delivery, and an SAP Fiori + Tableau inventory visibility improvement that cut 1,500 units of waste and saved $150K.”

“New grad SDE (AI/ML) who built and deployed an LLM-based chatbot framework used across technology, military, and banking contexts, focusing on model selection tradeoffs (latency vs accuracy) through prototyping and benchmarking. Also built a multi-agent "eaterybot" using PyAutoGen/AutoGen with a manager agent orchestrating specialized agents, and emphasizes rigorous testing with adversarial/edge-case datasets and hallucination checks.”

“Built production LLM systems including a real-time customer feedback analysis and workflow automation platform using RAG and multi-agent orchestration with confidence-based human escalation, addressing privacy and legacy integration challenges. Also automated ML operations with Airflow/Kubernetes (e.g., daily churn model retraining) cutting retraining time to under 30 minutes, and demonstrates a rigorous testing/monitoring approach plus strong non-technical stakeholder collaboration.”

“Built a production "sentinel insight engine" to tame information overload from millions of product reviews and support transcripts, combining Azure OpenAI (GPT-3.5) zero-shot classification with a fine-tuned T5 summarizer to generate weekly actionable product insights. Demonstrated strong MLOps/production engineering by adding drift monitoring with embedding-based detection, integrating REST with legacy SOAP/queue-based CRM via FastAPI middleware, and scaling reliably on Kubernetes with HPA.”

“Healthcare-focused data engineer/ML practitioner with experience at Lightbeam Health Solutions and Humana building production entity-resolution and semantic similarity pipelines across EMR, lab, and claims data. Uses NLP/ML (spaCy, scikit-learn, BioBERT/LightGBM) plus Snowflake/Airflow and vector search (Pinecone) to improve linkage accuracy (reported 90%) and semantic match quality (reported +12–15%), while reducing manual cleanup by 40%+.”

“Solo-built and launched an AI logo generator SaaS in ~2 months using React/Next.js/TypeScript with managed auth and payments, deploying via Vercel/GitHub CI/CD. Also has hands-on AWS production experience running containerized services with Terraform-managed multi-environment infrastructure and strong reliability patterns for integrations/pipelines.”

“QA automation engineer with end-to-end ownership of a loan-processing automation suite spanning UI, API, and database validations (Selenium/Playwright/TestNG/REST Assured; Java/Python). Caught and prevented high-impact financial defects (e.g., risk-calculation rounding errors) through CI-driven nightly regressions and API-to-DB checks, and has implemented maintainable Cypress patterns with flake reduction plus GitLab CI gating and Allure reporting.”

“Software engineer with Citi Bank experience building real-time fraud validation/scoring for loan processing, spanning Spring Boot microservices and a FastAPI Python service secured with OAuth2/JWT. Delivered React/TypeScript operations dashboards and deployed containerized services via Docker/Kubernetes with Jenkins CI/CD, while also tuning databases (Oracle/Postgres) and handling high-volume latency/scaling issues using ELK, caching, and autoscaling on AWS.”

“Providing technical guidance to a small team exploring a biomedical startup focused on earlier disease detection, including for remote/underserved areas. The venture is in ideation with initial research completed and is moving toward prototyping while exploring initial investment/support.”

“Cloud/Kubernetes-focused production engineer with experience running 99.95% uptime platforms across AWS/Azure/GCP. Strong in incident response and performance troubleshooting (including a 30% MTTR reduction), and in building secure CI/CD and Terraform-based IaC for AKS/GKE microservices with robust change controls and rollback practices. Notably does not have direct IBM Power/AIX/VIOS/HMC or PowerHA/HACMP ownership.”

“Backend-leaning product engineer with DevSecOps depth who has shipped real-time, Kafka-driven data pipelines and AI-enabled customer-facing features to production on AWS. Built a Spring Boot API layer serving real-time predictions at 100K+ requests/day, improving latency by 35% and user task completion by ~25%, and delivered a React/TypeScript dashboard plus a Postgres audit/history model optimized for search and large event volumes.”

“Backend/full-stack engineer with Blue Cross Blue Shield experience building a reactive, event-driven claims processing microservice platform on AWS (ECS, SNS/SQS) with Terraform-based IaC and strong observability (Dynatrace/CloudWatch). Demonstrated measurable production impact (32% less downtime, 24% higher processing efficiency) and deep database performance/migration expertise across MongoDB and Postgres.”

“Backend/AI engineer who owned a high-scale Java/Spring Boot microservice for a financial application (millions of requests/day) and led major reliability/performance fixes (including ORM/query and PostgreSQL tuning) achieving ~60% latency reduction. Also shipped application-layer LLM features for ops teams (summarization + tool-calling) with strong guardrails (PII redaction, validation, audit/feedback) and designed a state-driven agent workflow with retries, circuit breakers, and human escalation.”

“Backend/data platform engineer who led a major redesign of a hybrid streaming+batch analytics platform processing 10+ TB/day (Airflow/Hive/BigQuery) with strong data-quality automation. Also built a production RAG PDF assistant with concrete mitigations for hallucinations and prompt injection (re-ranking, grounding, verifier step) and has deep experience executing low-risk migrations (dual-write, blue-green, rapid rollback) and implementing JWT-based row-level security.”

“Built and deployed a production LLM-powered customer support assistant using a RAG backend in Python, focused on deflecting repetitive Tier-1 tickets and reducing resolution time. Demonstrates strong production engineering instincts around reliability (confidence scoring + human fallback), scalability/cost optimization (multi-stage pipelines), and workflow orchestration/observability (LangChain, custom DAGs, structured logging, step metrics).”

“Backend engineer who designed and evolved an AWS-based event-processing system in Python/PostgreSQL, achieving a 60% p95 latency reduction while improving reliability during traffic spikes. Led a zero-downtime migration from a monolithic Django app to FastAPI microservices using feature flags, strong testing, and cross-team coordination, with production-grade observability (Prometheus/Grafana/CloudWatch) and security (JWT/OAuth2, RBAC, Postgres RLS).”

“Backend/ML-leaning engineer who built a content-based event recommender for FlowMingle using embeddings + HNSW vector search on Google Cloud, with Firebase as the backend and a managed recommendation lifecycle (15 recs/user, daily async generation, weekly deletion) now serving 1500+ users. Also led a cost-driven migration of ConvAI services to Azure AI using parallel request testing from a Unity client, with post-migration monitoring via logs and model evals; contributed to a Massachusetts law-enforcement conversation analysis system by expanding ingestion to PDF/TXT/Excel and multi-file inputs.”