Vetted System Design Professionals

Ron Buchanan

Screened ReferencesStrong rec.

Executive technology leader specializing in cloud architecture and Healthcare IT

Summerville, SC20y exp

“Startup-focused builder currently developing a values-driven multi-platform mobile app in beta. Previously led a major technical turnaround at Lucina Analytics, taking the product from 0-to-1 and rebuilding it into an enterprise Azure-based SaaS platform that contributed to its acquisition by Unified Women's Health.”

“Product engineer/designer with founder mindset who shipped a blockchain-enabled investor group/governance platform using Next.js (App Router), TypeScript, Prisma/Postgres, and Temporal. Emphasizes auth-centric onboarding (SSO + embedded wallet) to make dApp UX feel more like SaaS, and brings strong reliability practices (idempotent retries, reconciliation) plus experience demoing to investors and operating in seed-stage teams (ex-Vouched).”

“Full-stack engineer with strong Next.js App Router/TypeScript experience who built production dataset search/filtering and data-heavy dashboards backed by Postgres. Demonstrates hands-on performance work across the stack (EXPLAIN ANALYZE, composite indexes, caching, React profiling/memoization) and has built durable, Temporal-like orchestrated data-processing workflows with idempotency and retry strategies in an early-stage startup environment (Gaia AI).”

“Early-career engineer who built and launched a zero-to-one AI-driven approval workflow at SDSU that is used daily by roughly 2,000 university users. They owned the system end-to-end—from FastAPI/PostgreSQL backend to React UI—and showed strong judgment around LLM reliability, using a two-step pipeline, validation checks, and human-review fallbacks to cut manual processing time by about 80%.”

shelly tomar

Screened

Mid-level Founding Engineer specializing in agentic AI for healthcare

null4y exp

“Founding engineer at Grosha who built and operated the backend from scratch, helping scale the product to 65+ countries in a fast-moving startup environment. Also brings healthcare AI experience from United Health Group, where they built backend pipelines for ambient AI scribing using transcription APIs and LLM orchestration with custom validation layers for clinical reliability.”

“Software engineer (Yellow.ai) who built and productionized an AI-driven resume tailoring system using embeddings + Chroma RAG + QLoRA fine-tuning, deployed via Docker/Kubernetes with CI/CD on a CPU-only Oracle VM. Demonstrates strong reliability/evaluation rigor (custom hallucination/coverage/relevance metrics) and measurable business impact, including a 60% user satisfaction lift from improving chatbot intent accuracy with product and support teams.”

“Master’s-program backend engineer with strong Java/Spring Boot industry experience who also owned a Python analytics service (Flask/Postgres, JWT, Celery/Redis) and optimized large-dataset performance via SQL/batching. Has hands-on Kubernetes microservices deployment and GitLab+Terraform CI/CD/GitOps workflows, plus experience supporting phased on-prem to AWS migrations and building Kafka-based real-time streaming pipelines.”

“Backend/ML platform engineer who owns end-to-end delivery of ML-serving APIs (FastAPI + TensorFlow) and runs them reliably on Kubernetes using ArgoCD GitOps. Has hands-on experience solving production-only issues (probe tuning for model warm-up, resource profiling) and building scalable Kafka streaming pipelines, plus supporting phased on-prem to AWS migrations with dependency discovery and recreation of hidden jobs/workflows.”

“Software engineer with connected-car/automotive production experience who owned an end-to-end remote door lock/unlock feature and introduced unit testing (GTest) plus rig/simulator validation. Also built and productionized an AI-native AWS cloud cost assistant (Lex + GPT-based LLM + Lambda + RAG/vector DB) with guardrails and achieved 94% evaluation accuracy. Helped replace a third-party solution with an in-house build, saving the company ~€9M.”

Sowmya Kasu

Screened

Mid-Level Software Engineer specializing in Healthcare IT and cloud-native microservices

Northridge, CA6y exp

“Backend/ML engineer with healthcare experience at Kaiser Permanente building HIPAA-compliant Java/Spring Boot + GraphQL APIs integrated with Epic HealthConnect, including hands-on reliability/performance debugging using Prometheus/Grafana and resolver-level N+1 elimination. Also built an end-to-end malaria parasite detection ML feature (CNN/R-CNN) with evaluation, guardrails, and workflow integration, and has experience designing robust state-machine-based automation with retries, DLQs, and alerting.”

Sai Erramada

Screened

Mid-level Full-Stack Java Developer specializing in microservices and cloud-native systems

Wisconsin, USA6y exp

“Backend engineer with hands-on experience building real-time, event-driven systems at Walgreens, including a Kafka-based prescription status notification service and scalable pipelines for messy prescription/inventory data. Strong focus on reliability patterns (retries, idempotency, DLQs) and iterating based on pharmacist feedback to improve usability.”

Sandipkumar Prajapati

Screened

Mid-Level Software Engineer specializing in full-stack systems and authentication

New York City, NY4y exp

“Full-stack engineer who led production modernization of a legacy, latency-sensitive application into a React + microservices platform, with heavy TypeScript backend work to improve reliability and maintainability. Has operated and scaled authentication/identity services in production, addressing peak-traffic latency spikes via database tuning and improved observability, and emphasizes idempotent, retry-safe workflow design.”

“Built and shipped LLM-enabled decision systems focused on real production reliability rather than chatbot demos, including a multimodal radiology retrieval platform with 28% relevance gains and 35% lower latency. Also architected a 4-agent employee analytics workflow with structured outputs, traceable orchestration, and strong safeguards for messy real-world data.”

“Built and shipped a production LLM-powered email automation agent for procurement that ingests emails/attachments, classifies requests via rules+embeddings+LLM fallback, enriches responses with SAP inventory data, and generates templated replies. Architected it as an event-driven, idempotent Azure Functions/Queues pipeline with schema-constrained outputs, confidence gating, retries/circuit breakers, and Application Insights monitoring—cutting turnaround time from 4–7 days to near real-time while maintaining zero downtime.”

“Full-stack AI engineer who has owned production deployments for both a voice journaling/emotional insights app and a RAG-based research assistant. Stands out for turning messy, failure-prone LLM and document pipelines into reliable user-facing systems through strong debugging, staged workflow design, and post-launch stabilization.”

“Built production AI agents that convert natural-language requests into structured workflows using LangChain, tool calling, and a Kafka/Kubernetes backend, with strong emphasis on tracing, validation, and self-correcting failure handling. Also drove a zero-to-one Research Day judging platform spanning React, Flask, RAG, and ILP-based assignment optimization for ~100 live posters, achieving 99% uptime and winning Best Web App.”