Vetted System Design Professionals

Abhishek Yadav

Screened ReferencesStrong rec.

Mid-level Full-Stack Engineer specializing in Python and FinTech

Tempe, AZ4y exp

“Full-stack engineer with experience shipping both enterprise financial systems at Citi and production AI copilots. Built a real-time transaction monitoring dashboard that cut manual reporting by ~60%, and also designed a grounded, human-in-the-loop LLM support assistant with RAG, structured outputs, and production evals for quality and compliance.”

“Full-stack builder with a strong hackathon track record who has shipped user-facing products in healthcare and geopolitical risk analysis. Built a telehealth symptom-to-care routing app using Python NLP and a React/TypeScript stack, and also created OrbisScope, a HackRU 2025-winning platform that analyzed 1M+ records from 30+ live RSS feeds with 98% predictive accuracy.”

“Frontend tech lead at HubSpot who shipped an LLM-powered insights dashboard that analyzed complex customer interaction histories and surfaced sentiment, challenges, and next-best actions for sales users. Stands out for having taken an AI feature beyond prototype into beta and full production, with strong emphasis on testing, maintainability, and practical production tradeoffs.”

“Candidate has developed a disciplined AI-first engineering workflow that combines design docs, prior PR analysis, testing plans, and multi-agent coordination to accelerate delivery without sacrificing quality. They described acting as a tech lead for AI agents, overseeing code structure, business logic, testing, and service contracts, and reported reducing manual coding effort by nearly 80%.”

“Full-stack builder with hands-on experience shipping both location-based consumer products and AI-driven data platforms. Has owned end-to-end systems across React/Next.js, FastAPI, PostgreSQL, Streamlit, and geospatial tooling, with a strong emphasis on modular architecture, LLM reliability, and turning messy real-world data into usable product experiences.”

“Full-stack engineer with startup-style experience building assessment and learning platforms using React, Node.js, Python, MongoDB, and PostgreSQL. Stands out for owning backend auto-grading and analytics features end to end, including concurrency-safe submission processing and database performance optimization for growing datasets.”

“Full-stack/backend-leaning engineer who has built internal operational dashboards and AI assistants, including a real-time dashboard used by engineering, operations, and management teams at NVIDIA. Brings a mix of Spring Boot, Angular/TypeScript, distributed-system performance tuning, and practical LLM integration with grounding, validation, and production monitoring.”

“Safety-critical firmware validation engineer with Tesla autonomous vehicle experience who built Python-based HIL/SIL automation and dashboards, cutting regression time by 30% while maintaining an auditable risk-tradeoff process with safety and engineering teams. Also deployed an inventory management system across 8+ R&D teams in 3 countries at FUJIFILM, troubleshooting a major cross-site sync issue to a timezone root cause with strong documentation and interim mitigations.”

“Full-stack engineer in the investment tracking/financial reporting space who built an automated reporting dashboard and compliance/reporting pipeline end-to-end using Next.js (App Router, server/client components), REST, and Postgres. Demonstrated measurable performance wins (~30% faster loads) through caching and query optimization, and built durable orchestrated workflows in n8n with retries, idempotency, and reconciliation checks.”

“Built a production AI-powered workflow automation system at Netflix that integrated OpenAI and LangChain with FastAPI services on AWS, cutting roughly 320 hours of manual operational effort. Brings a mix of full-stack product development and practical AI systems experience, with strong attention to reliability, maintainability, and non-technical user adoption.”

“Backend owner at Apple for an AI workflow orchestration service, with hands-on experience stabilizing peak-traffic production systems using OpenTelemetry-style tracing, bounded async concurrency, and database performance tuning. Built and shipped a Python LLM-agent orchestration layer to automate multi-step operational workflows, emphasizing guardrails, auditability, and deterministic fallbacks to keep non-deterministic AI behavior production-safe.”

Jehanzeb Khan

Screened

Director-level Engineering Manager specializing in large-scale data and compute platforms

Sunnyvale, CA20y exp

“Platform and distributed-systems leader (player-coach) who owned architecture and reliability for an Amazon analytics/data platform serving ~100K internal users at exabyte scale. Built an ML-driven “Lakeflow” optimization layer that cut pipeline completion times ~20–25% and reduced compute waste >15%, and led major incident response/redesign efforts (e.g., deletion storm) with strong rollout/observability/rollback practices.”

Shivam Gupta

Screened

Mid-level Software Engineer specializing in distributed systems, AI, and FinTech

USA5y exp

“Full-stack engineer with experience at AWS and Barclays, spanning large-scale cloud infrastructure, customer-facing product development, and production GenAI systems. Stands out for owning systems end-to-end—from backend architecture and frontend UX to AI reliability and cost optimization—with measurable impact including 25% fewer support tickets, 10% subscription growth, and debugging time reduced from 30 minutes to 5 minutes.”

“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.”

“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.”

“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.”

“UI/UX and product-minded designer with experience shaping digital products from concept to launch across telecom and higher education. Notably pitched a new Globe Telecom app that became the basis for the product after joining, helped launch it within five months, and contributed to a 4x subscription lift through A/B-tested in-flow upsell design.”

“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 production LLM systems focused on reliability and safety, including a plain-English deployment tool that generates validated plans and provisions to Kubernetes while preventing unsafe actions via schema enforcement and plan/execute separation. Also created multi-LLM workflows (LangGraph) and stakeholder-friendly demos at Bosch, including a PyQt/FastAPI/CUDA app comparing SAM2 vs SAMWISE for on-device object detection with intuitive UX for business users.”

“Backend/data engineer who has owned production Python APIs and high-throughput async workflows on AWS (FastAPI, Docker, ECS/EKS/Lambda) with mature reliability practices like idempotency, bounded retries, circuit breakers, and strong observability. Also built AWS Glue ETL into an S3/Redshift lakehouse and modernized legacy batch systems via parallel-run parity testing and feature-flagged migrations, including a SQL tuning win cutting a multi-minute query to under 10 seconds.”

Joseph Leybovich

Screened

Senior Unity Engineer specializing in XR and game development

Culver City, CA13y exp

“Unity/C# gameplay engineer with hands-on experience shipping end-to-end game systems, including a story mode pipeline on Marvel Mighty Heroes that supported designers directly and improved player retention. Also brings experimental AI/LLM and VR experience from Meta hackathons plus Photon multiplayer and cross-platform VR/mobile prototyping expertise.”

“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.”

“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.”