Vetted Database Schema Design Professionals

Dylan Jaworski

Screened

Intern Software Engineer specializing in Python data pipelines and backend systems

Tallahassee, FL0y exp

“Software engineering intern at the Florida Department of Transportation who built validation/anomaly-detection logic for a live operational telemetry + system log processing pipeline. Emphasizes fault-tolerant, state-driven system design (degraded modes, data freshness tracking, safe fallbacks) and debugs time-sensitive behavior via logging/latency analysis and replay-based testing—skills that translate well to robotics-style architectures despite no direct ROS/robot experience.”

“Backend engineer who owned the API layer for an AI trust/analytics dashboard (trust scores, stability checks, public verification endpoints) using Python/FastAPI and Postgres. Has hands-on DevOps experience deploying FastAPI and Node.js services to AWS Kubernetes with GitHub Actions + ArgoCD GitOps, plus Kafka-based real-time event streaming and careful staged migration practices (shadow traffic/dual writes, rollback planning).”

Umair Azam

Screened

Senior Full-Stack Software Engineer specializing in Ruby on Rails and React

Lahore, Pakistan10y exp

“Frontend engineer with React/TypeScript experience who has led end-to-end UI work on a fintech product (React frontend with NestJS APIs), emphasizing performance (virtualized rendering, memoization, lazy loading, profiling) and quality at scale (unit tests and TDD). Also built and iterated on a snooker sports app, simplifying UX through audience-focused design decisions and streamlined onboarding.”

William Watanabe

Screened

Mid-level Full-Stack Software Engineer specializing in authentication and SolidJS/TypeScript

New York City, NY3y exp

“Mid-level full-stack engineer (Los Angeles) who built and shipped an end-to-end authentication system for SolidAuth, an open-source SolidStart ecosystem library published to NPM with 1000+ downloads. Experienced designing React/TypeScript + Node + Postgres architectures, operating lightweight production systems on AWS (EC2/S3/RDS/IAM/CloudWatch), and building resilient third-party ingestion/integration flows with idempotency, retries, queues, and backfills; also worked in an early-stage NIL startup (OFFSZN) shipping core onboarding/profile features amid changing requirements.”

Sampath Achalla

Screened

Mid-level Python Full-Stack Engineer specializing in AI microservices and cloud data platforms

USA3y exp

“Backend-leaning full-stack engineer in fintech/payments who shipped an end-to-end Stripe payments + webhook system for a financial microservices platform, emphasizing ledger accuracy via idempotency, transactional writes, retries, and DLQs. Also delivered a real-time React/TypeScript payment status dashboard informed by user interviews, and improved production performance by 35% p95 latency through PostgreSQL tuning and Redis caching on AWS.”

Merub SHAIKH

Screened

Junior Software Engineer specializing in full-stack web development and test automation

Chicago, IL3y exp

“Full-stack engineer who built and owned a production workflow/kanban-style drag-and-drop system in Next.js (App Router) with Postgres/Prisma, including reusable component abstractions, Cypress E2E coverage, and post-launch performance/bug ownership. Notable for measurable impact (25% faster UI dev, ~30% query perf improvement) and for leading an incremental Express→NestJS migration that reduced technical debt (~40%) through better structure, docs, and team enablement.”

“Software/product engineer who has owned a consumer iOS dating app from customer discovery through roadmap execution, while also shipping an in-app LLM-powered support/feedback bot. Brings a mix of product sense and backend systems experience, including rebuilding a race-condition-prone event orchestration system and designing microservices to handle arbitrary black-box production data.”

“Frontend engineer at LodestonePM who led end-to-end delivery of an AI release-notes generator (OpenAI API) and a Kanban-style release board in Remix/React/TypeScript. Demonstrated scalable architecture (bridging tables, upserts), strong QA practices, and measurable performance wins (200+ item loads reduced from 10–20s to a few seconds via caching/pagination), plus UX improvements like simplifying a Jira integration flow.”

“Backend Python engineer who owned the full backend build of an AI-driven platform for UK golf clubs, including FastAPI microservices, vector search, and a tuned LangChain+Pinecone RAG pipeline focused on cost and hallucination reduction. Experienced deploying Django/FastAPI/Flask stacks on AWS-backed Kubernetes with GitOps/ArgoCD-style delivery, plus executing legacy-to-AWS migrations and building Kafka-based real-time analytics pipelines.”

“Full-stack engineer focused on Next.js (App Router) and TypeScript who has shipped and owned production role-based dashboards end-to-end, including post-launch reliability/performance work. Demonstrated measurable UI performance improvements (35–40% faster initial load) and strong backend rigor with Postgres query/index optimization (300ms to 30ms) plus durable Temporal-orchestrated onboarding/data-sync workflows with idempotency and retry strategy.”

“Built and shipped a production LLM-powered incident response agent for a microservices platform, automating alert triage and safe remediation recommendations with strong guardrails (RAG grounding, structured JSON outputs, rule-based validation, and human-in-the-loop). Implemented state-machine orchestration (Redis/Kafka), comprehensive eval/monitoring, and an error categorization pipeline that cut hallucination errors ~40% and reduced MTTR ~30%.”

CharanKumar Pathakamuri

Screened

Entry-Level GenAI/LLM Engineer specializing in agentic systems and RAG

Baltimore, MD1y exp

“LLM/AI agent engineer with consulting/contract experience (Kanhaiya Consulting LLC) who deployed a production AI agent to automate BIM list workflows end-to-end—from database understanding and data cleaning to automated visualizations/dashboards. Worked around restricted real-time data access by generating synthetic data and improving outputs via supervised fine-tuning, and uses AWS-based LLMOps observability (Opic/OPEC) plus hybrid retrieval (vector+BM25 with reranking) to optimize relevance, latency, and cost.”

Ajay Kudapa

Screened

Mid-level Software Engineer specializing in Healthcare IT and Web3

4y exp

“Software engineer with experience spanning healthcare middleware (patient records + insurance integration) and an AI fantasy football product built with React/TypeScript, Firebase, API gateways, and pandas-based data pipelines. Has hands-on microservices scaling experience (latency mitigation, async migration, state-based redesign) and built an internal feature-toggle dashboard that improved demo efficiency and sales outcomes.”

“Product-minded full-stack engineer with hospitality tech experience who owned and scaled a multi-region guest verification/check-in workflow (ID/passport scanning, OCR, and government submissions) and built internal tools that cut manual entry up to 80%. Also built a React/TypeScript + FastAPI RAG “second brain” with async ingestion workers and an event-driven e-folio email microservice hardened with idempotency and retries.”

“Backend/DevOps-leaning engineer who has owned a Python serverless platform on AWS (Lambda, DynamoDB, Step Functions), including complex multi-step business workflows with transaction-based consistency and robust failure handling. Also supported an on-prem SQL to Azure Data Lake migration by building and monitoring Python + Azure Data Factory ETL pipelines, and led GitOps-style CI/CD automation with GitHub Actions (tests, security scans, automated deployments).”

“Led a government smart city deployment where success depended less on pure engineering and more on navigating policy, budget, and operational constraints. Built phased, cost-conscious systems combining data pipelines, on-prem AI, OCR, and human-in-the-loop workflows to deliver stable production outcomes and make ambiguous real-world data more controllable at scale.”

“Built a production-grade clinical and insurance document AI system in a HIPAA/PHI-regulated environment, taking it from experimentation through Azure deployment, monitoring, and iterative improvement. Stands out for translating RAG/LLM research into reliable microservices with strong safety controls, drift monitoring, and human-in-the-loop workflows that cut manual review time by 60-70%.”