Vetted Distributed Systems Professionals

Meredith Ma

Screened

Entry-level AI/ML Software Engineer specializing in generative AI and computer vision

Pittsburgh, PA2y exp

“Built and owned a production RAG coding assistant at Magna International used by 200 engineers, with hands-on work across React/TypeScript, retrieval infrastructure, and Postgres observability. Also brings an unusual blend of product UX thinking from AR game onboarding work, showing strength in both technical systems reliability and user activation.”

“Software Developer at Amazon Robotics who co-developed a congestion-aware path planning system optimizing robot routes across 23 warehouses. Built and operated a real-time, service-integrated pipeline using AWS (AppConfig, DynamoDB), Java, and Redis caching, and has hands-on experience debugging robot behavior on-site with rigorous testing and staged releases.”

“CMU IoT coursework project builder who implemented an end-to-end TinyML gesture recognition system on a Particle Photon + ADXL345, streaming data via MQTT/Node-RED to a real-time Node.js frontend and deploying a quantized logistic regression model on-device. Also explored multi-drone coordination, implementing leader-follower offset control and a pivot/arc turning strategy to avoid collisions, and brings practical Docker/Kubernetes plus CI/CD workflow experience from internships.”

“Internship experience deploying cloud-based services into production, including navigating security/resource provisioning and coordinating approvals across impacted teams. Built a Python backend for a local Ollama-based app using open-source models, and has hands-on distributed systems experience implementing and debugging Paxos with extensive logging/state tracing.”

“AWS engineer who productionized an internal ML-driven data pipeline from a notebook prototype into a scalable, observable Python service (schema validation, deduplication, idempotency, safe retries, versioned transforms, CloudWatch alarms), reducing manual effort and improving data accuracy/trust. Experienced diagnosing workflow issues in real time (e.g., upstream schema changes) and partnering with account managers/support to unblock adoption of seller-facing Marketplace features by demonstrating reliability with concrete metrics.”

“Senior engineering leader in the Bay Area with experience spanning VMware, Hortonworks/Cloudera, Barracuda, and Palo Alto Networks, including leading open-source work (Apache Knox) and architecting large-scale security platforms. Has driven disaster recovery and cloud security products, designed Python microservices for Microsoft 365 security, and scaled teams (3x) while formalizing enterprise readiness practices with automated documentation using Notebook LLM.”

Jay Desai

Screened

Executive Technology Architect specializing in FinTech, AI platforms, and cloud modernization

California, USA24y exp

“Entrepreneur building an early-stage community food-sharing, network-effects platform positioned as an alternative to restaurant-centric delivery models (e.g., DoorDash/Uber Eats) by enabling homeowners to act as micro-entrepreneurs. Has been piloting a local community program for nearly a year and uses experiments and customer feedback to validate hypotheses and assess scalability.”

“Aspiring founder building an AI governance and compliance startup for the finance industry, focused on agents that monitor data lakes/lakehouses to detect security vulnerabilities, PII exposure, and governance issues in real time. Has already formed an S-corp, has not raised capital yet, and approaches idea validation through Minimum Lovable Product testing with potential clients.”

“Candidate describes a development approach centered on AI-assisted coding, testing, and agent-driven workflows, including production exposure to multi-agent systems and governance-oriented logging. They appear particularly focused on combining AI speed with structured validation through unit tests, boundary tests, and edge-case monitoring.”

Yashwanth J

Screened

Mid-level Software Engineer specializing in AI/ML and full-stack systems

Seattle, WA4y exp

“Engineer with Apple experience building LLM-powered internal workflow orchestration systems using Python, LangGraph, FastAPI, Redis, vector search, and Kubernetes. Stands out for a highly pragmatic, production-focused approach to agentic systems: deterministic state management, strong guardrails, observability, and human review for high-risk actions.”

“Senior frontend engineer focused on complex internal operations and payment products, with deep experience building React/TypeScript dashboards for payments, subscriptions, and observability workflows. Stands out for going beyond UI implementation to shape API contracts, real-time architectures, performance strategy, and product behavior across support, finance, and engineering use cases.”

“Built and productionized a dual-agent LLM invoice-processing system for GFI Partners, adding guardrails and audit trails to earn stakeholder trust and drive adoption while cutting operational burden by 75%. Uses LangSmith observability to diagnose real-time workflow regressions and has experience teaching agentic AI concepts (e.g., at Carnegie Mellon) through hands-on, scaffolded demos.”

“Software engineer with 2.5 years at Amazon working on the Package Tracking page (Amazon’s most visited page), delivering new customer actions like Cancel Delivery and Buy Again within a Spring Boot-based stack. Has hands-on experience with feature-flagged rollouts (Weblab), A/B testing, and scaling/load testing for Prime Day-level traffic, and is upskilling into React while leveraging modern AI coding tools on side projects.”

“Full-stack engineer (Snowflake) who shipped an AI/LLM-powered data exploration product end-to-end, spanning Spring Boot/Python services and a polished React UI with streaming responses and robust fallbacks. Experienced operating high-scale AWS deployments (Docker/Kubernetes, SNS/SQS, RDS Postgres, CloudWatch, Jenkins CI/CD) supporting thousands to tens of thousands of concurrent users, including handling real traffic-spike scaling incidents.”

“ML/LLM engineer with production experience building a multi-GPU LLM inference platform using TensorRT and vLLM, achieving ~40% p95 latency reduction through batching/KV caching, quantization, and CUDA/runtime tuning. Also has end-to-end orchestration experience (Kubernetes, Airflow) and has delivered real-time fraud detection systems at Accenture in close collaboration with non-technical risk and product stakeholders.”

Michael Kilgore

Screened

Mid-Level Software Development Engineer specializing in AWS data pipelines and forecasting systems

3y exp

“Built and deployed (via an Upwork contract) an LLM-powered agent for options trading that detects large options trade events, enriches them with market/filing data (price history, earnings transcripts, insider trading), and delivers recommendations via Telegram. Implemented schema-constrained outputs (Pydantic/Google GenAI), robust orchestration, logging, and error-notification handling, plus vector-DB-based reuse of prior outputs to improve consistency.”

“Engineering leader with experience at CBS Interactive and Paramount who scaled a web engineering team from 4 to 30+ (adding QA/PMO/mobile) while instituting strong agile and code-quality processes. Led a major architectural shift to a generic content API that decoupled web/mobile experiences from niche publishing systems, reportedly cutting developer onboarding time by ~50% and enabling some day-one production commits.”

Robert Davis

Screened

Staff Software Engineer specializing in backend and distributed systems

Remote, US19y exp

“Backend engineer who co-launched SkyKick’s Office 365 SharePoint/Exchange backup product, built the MVP, and then architected and led its design for 9 years. Stands out for high-scale systems expertise, including an algorithmic redesign that cut cloud costs by an order of magnitude, plus earlier experience integrating speech recognition systems in noisy real-world customer environments.”

“Senior software engineer candidate who uses AI and multi-agent workflows thoughtfully to speed up development while preserving engineering rigor for production-critical decisions. Stands out for a clear risk-based framework: leveraging agents for boilerplate, refactoring, testing, and debugging, while relying on fundamentals, metrics, and human review for system design and scalability.”

“Solutions engineer with recent experience in semiconductor and manufacturing SaaS, spanning pre-sales demos, SOW/POC authoring, on-site deployments, and production integrations. Particularly notable for bridging factory-floor equipment, on-prem Java applications, and Azure cloud systems, while also operating in highly regulated NIST 800-53 defense environments.”

“Software engineer with experience spanning early-stage startup architecture and large-scale Amazon product development. They’ve driven search and data-platform decisions in a 20-person startup, built full-stack React/Python tools that automate internal workflows, and shipped marketplace expansion and personalization features impacting 200k sellers and millions of end users.”

“Full-stack engineer with experience spanning a lean startup at AppLovin and production financial systems at Vanguard. They’ve built core user-facing platforms from scratch, including a B2B advertiser/publisher dashboard and a resilient client onboarding system using Spring Boot, NestJS, Postgres, Kafka, Redis, and AWS. Particularly strong in ambiguous environments where they work directly with stakeholders and own delivery end to end.”