Vetted System Design Professionals

Mathew Martin

Screened

Mid-level Software Engineer specializing in cloud data platforms and LLM applications

New York, USA4y exp

“LLM/agent builder with experience shipping production LLM features at an early-stage ed-tech mental wellness startup (conversation analysis + structured feedback via FastAPI, OpenAI API, Render, CI/CD). Also built a multi-step dining concierge agent using OpenSearch over Yelp data with fallback query relaxation, and has enterprise data engineering experience at Capgemini migrating databases to Snowflake with robust ETL normalization and data-quality handling.”

“Currently at Berryble AI, this candidate is building an LLM-based real-time interview analysis engine using FastAPI, WebSockets, fine-tuned models, and GCP/Cloud Run. They stand out for using AI and agent workflows pragmatically to accelerate development while keeping human ownership over architecture, security, reliability, and maintainability, and they are also pursuing a master's in applied machine learning.”

“Built production-scale dashboards and real-time data systems across fintech and autonomous driving, with hands-on ownership from React frontend architecture through Python/Kafka/Elasticsearch backend pipelines. At Zoox, led development of an automated safety signal attribution platform that replaced manual engineering calculations and surfaced trends through dashboards.”

“Hands-on engineering leader who has scaled teams quickly (hired 20 engineers in 4 months) and led major architecture shifts including monolith-to-microservices and serverless, async AI-driven medical data ingestion/search. Also drove a versioned-inventory redesign with auditability and rollback that reduced operational errors by 22%, and demonstrates strong incident response with clear stakeholder communication.”

“Frontend/full-stack product engineer with deep experience owning payment and subscription experiences across web, mobile, and BFF layers at SoFi. They helped shape the SoFi Plus subscription experience, including API contracts, observability, and complex membership state handling, and the launch was associated with roughly 200,000 new members over six months.”

Ilya Kravchenko

Screened

Executive engineering leader specializing in AI-enabled SaaS and internet-scale platforms

Thousand Oaks, CA20y exp

“Engineering leader with a rare blend of SaaS, robotics, and AI systems experience, most recently leading a 21-engineer org under the CTO. They pair strong people/process leadership with hands-on architecture depth, driving dramatic delivery improvements while also building grounded LLM support tooling for warehouse operations where accuracy directly impacts physical execution and customer outcomes.”

Keerthana Kondabathini

Screened

Senior Full-Stack Engineer specializing in healthcare and financial platforms

5y exp

“Software engineer with experience spanning healthcare platforms at UnitedHealth Group/Optum and B2B SaaS systems at Zoho. Has worked on a startup-like internal product for intelligent medical document processing using microservices on Azure, while also building React dashboards, backend APIs, and Python automation to support clinical and business operations.”

“Full-stack engineer with hands-on ownership of an internal LLM platform, spanning React/NestJS development, PostgreSQL schema design, multi-provider model integrations, and chat/eval pipelines. They also show strong production engineering instincts, having resolved Cognito throttling failures via tracing and led an observability migration to Signoz that materially improved incident diagnosis speed.”

Aaron Mcanerney

Screened

Mid-level Backend Software Engineer specializing in data platforms and reporting

Pleasanton, CA5y exp

“Built a production Medicare Q&A chatbot using OCR (pytesseract), LangChain chunking, ChromaDB embeddings/retrieval, and an Ollama LLM. Thinks in terms of practical tradeoffs (cost, model selection, static vs frequently-updated corpora) and emphasizes deterministic testing plus observability for reliable LLM workflows; also has experience automating non-technical teams' pain points (e.g., recruiting event integration).”

“Built and owned end-to-end production Conversational AI and RAG systems at Nike for customer support and product search, with strong evidence of measurable impact. Combines LLM product thinking with solid platform engineering, including evaluation pipelines, monitoring, safety controls, and reusable FastAPI frameworks that improved both user outcomes and team velocity.”

“Senior product leader with deep payroll/HCM experience across ResNav, Paycom, Paylocity, and Namely, known for rebuilding broken systems, creating product process from scratch, and influencing boards and executives on major platform decisions. She combines hands-on prototyping, strong engineering partnership, and customer-driven iteration, with examples ranging from an ML-based approvals workflow that reached 100% client opt-in to stabilizing a troubled time-off platform and reducing churn risk among major revenue clients.”