Vetted Event-Driven Architecture Professionals

“Startup-focused engineering leader applying for a CTO role; previously served as founding CTO of a tech startup and held engineering/architecture roles across several others. Evaluates new ventures through market research and market demand, and emphasizes building from the ground up with strong teams (has not personally participated in fundraising).”

“Works on clinical trial applications and data pipelines, including AWS Lambda-based file transfer workflows for clinical study metadata. Has hands-on experience hardening production systems by adding observability, SSH/auth exception handling (Paramiko), retries/timeouts, and validating changes across SIT/UAT/prod. Also supports adoption through tailored technical demos for new teams and vendor partners integrating into their workflows.”

“Backend/platform engineer with payments and insurance domain experience (Cognizant), owning high-volume production systems end-to-end. Shipped a Spring Boot payment tokenization service with strong observability and phased migration that cut transaction latency ~30% and improved payment efficiency ~25%. Also productionized an ML-driven financial health/risk analytics pipeline with near real-time dashboards across 70+ schools, emphasizing interpretability, data quality, and drift monitoring.”

“Backend-focused Python engineer who owned high-traffic internal services end-to-end (FastAPI/Django) including REST/GraphQL APIs, PostgreSQL optimization, async task processing via SQS, and full CI/CD. Strong Kubernetes-on-EKS and GitOps (ArgoCD + Helm) experience, plus Kafka real-time streaming work and phased cloud-to-on-prem migration support.”

“Full-stack engineer who builds and scales customer-facing and internal AI products end-to-end (React/TypeScript/FastAPI/MongoDB) with strong product instrumentation and rapid MVP iteration. Built an AI-powered code review assistant adopted across teams and integrated into CI/CD, reducing manual review time by 30%+, and has hands-on experience with LLM retrieval/reasoning systems (LangChain + FAISS) and microservices scaling using RabbitMQ, Docker, and AWS.”

“Built a production agentic AI assistant in Python using Playwright plus Google Gemini’s vision capabilities to automatically document and execute UI workflows step-by-step, reducing developer time spent on trivial documentation/knowledge transfer. Also built an Apache Airflow ETL pipeline and has experience evaluating AI agents with human-in-the-loop methods, plus successfully communicated a vision-model-based CMS analytics PoC to non-technical university stakeholders and proposed it to Academic Technology with cost-savings rationale.”

“Backend-leaning full-stack engineer who builds and operates Spring Boot microservices with React/TypeScript frontends, using Kafka/RabbitMQ for event-driven workflows. Created an internal ops dashboard for Support/SRE with tracing, alert correlation, and self-serve actions, improving MTTR and reducing escalations while maintaining regulatory-grade reliability and security.”

“Frontend-focused engineer who has delivered an end-to-end React SPA with a .NET 9 backend on Azure, deploying via Azure Container Apps and leveraging zero-downtime deployment slots. Built complex TypeScript UI flows (10-page form with global/partial save and custom validation) using Redux + MUI integrated from Figma, and emphasizes quality with RTL/Vitest plus Selenium automation (~95% coverage) and analytics-driven iteration (Heap, Alida, GTM).”

“Backend/data engineer who built an enterprise LLM assistant (AI Genie) at Broadband Insights using a LangChain + GPT-4 + Pinecone RAG pipeline to automate broadband analytics reporting. Developed Python/Dagster ETL processing 10M+ records/day and improved data freshness by 60%, with production-grade scalability patterns (async workers, containerized microservices, Kubernetes) and strong multi-tenant isolation practices.”

“Backend engineer with fintech/AI startup experience who built an Azure serverless, event-driven pipeline for large-scale crypto sentiment analysis and semantic search (OCR/NLP to vector search) and integrated LLM + blockchain data for predictive insights. Demonstrated measurable impact (25% lower retrieval latency, 10% fewer data errors, 15% higher engagement) and has led safe microservices migrations with strong security and reliability practices.”

“Backend/data engineer with strong production experience across Python microservices (FastAPI) and AWS serverless/data platforms (Lambda, API Gateway, Glue, Redshift). Demonstrates reliability and incident ownership (rate limits, retries/circuit breakers, monitoring) and has delivered measurable SQL performance gains (12–15s to <800ms, ~60% CPU reduction). Seeking fully remote work and not open to relocation/onsite meetings.”

“Frontend engineer/product lead with experience building a Tableau-like data visualization dashboard at StradigiAI, including a scalable SQL-like query/filter approach for high-volume data. At LogMeIn/GoTo, migrated a TypeScript React product from Redux to React Query with shared state abstractions across web, Electron, and React Native, and helped leverage a design system to support a rapid company rebrand.”

“Unity game developer focused on single-player casual/hyper-casual titles for TV and mobile platforms. Built an event-driven, modular progression/time-access system spanning rewards and monetization (daily rewards, subscriptions, one-time offers) and emphasizes mobile performance optimization using Unity Profiler, pooling, memory tuning, and Addressables; uses AI to prototype/validate time-based system approaches.”

“Frontend engineer who delivers quickly on high-stakes, client-driven projects—led a payment request frontend rewrite shipped in 1–2 weeks and implemented a pre-authorization management feature on a one-week deadline. Experienced in Vue + TypeScript (with React exposure) and in improving existing codebases by standardizing state management (Pinia), while also owning dev-led QA, deployments/rollbacks, and close collaboration with product/design via Figma.”

“Master’s program project lead who built and deployed a real-time sound recognition system (Flask + React Native + ML) that was adopted by 200+ university students. Demonstrates strong production engineering and cross-layer debugging—solving latency, unreliable uploads, and observability gaps using microservice separation, chunked/idempotent transfers, and packet-capture-driven network diagnosis—plus AWS/on-prem and IoT edge-to-cloud integration experience.”

“Backend Python engineer who architected an event-driven order integration engine connecting EDI vendors to ERP/WMS/3PL systems, including a canonical order model and adapter framework to eliminate per-customer hardcoding. Has hands-on Kubernetes production experience (microservices, Celery workers, CronJobs, HPAs) and implemented GitOps/CI-CD using GitHub Actions, Docker, and ArgoCD, including moving deployments from on-prem to Azure.”

“Full-stack engineer who built a cloud-native customer servicing platform at Synchrony using React 18/Next.js (SSR) and Spring Boot microservices on AWS. Experienced with high-volume, event-driven systems (Lambda/SNS/SQS) and strong distributed-systems rigor around data integrity (idempotency, DynamoDB conditional writes) plus production-grade security/observability (JWT/OAuth2, WAF, Actuator, Splunk).”

“Software engineer with enterprise, customer-facing delivery experience across Outlier AI and Wipro—builds and productionizes workflow and integration solutions with a strong focus on real-world performance and reliability. Delivered a Firestore/Redis-backed real-time pipeline that cut page load times by 20% and held consistent performance across 10,000+ sessions, and has hands-on production incident experience stabilizing high-traffic microservices via caching, indexing, and safe canary deployments.”

“LLM/RAG-focused engineer who repeatedly takes agentic workflows from impressive demos to dependable production using rigorous evals, SLOs, and deep observability. Has led high-impact incident mitigation (22-minute MTTR during a major sale) and developer enablement workshops, and partnered with sales to close a $410k ARR enterprise deal with a tailored RAG pilot (FastAPI/pgvector/Okta/InfoSec-ready).”

“Technology leader with experience driving multi-year transformations at Jewelry Supply, including migrating a legacy custom e-commerce platform to SaaS and leading a 3-year ERP program from requirements through implementation and training. Also led a major architecture shift from self-hosted virtualized infrastructure to cloud Kubernetes with a strong DevOps/DevEx focus, emphasizing stakeholder buy-in and scalable processes for distributed engineering teams.”

“Gameplay/systems developer with shipped VR experience on Meta Quest (Litesport), owning a real-time workout scoring and progression system end-to-end including hit validation, HUD/UI, session state, and persistence. Known for event-driven architecture that decouples gameplay from UI, data-driven tunables for multiple modes, and rigorous VR performance work to hold 72 FPS using on-device profiling and debugging.”

“Backend developer (recent co-op at Ticker) building and architecting financial backend services with near real-time data needs, including third-party API integrations. Improved performance and reliability via Redis caching (tiered refresh + TTL) and PostgreSQL query tuning (EXPLAIN ANALYZE + composite indexes), and has exposure to AI-agent/RAG concepts for validating stock-market information against trusted sources.”

“Backend-focused TypeScript/Node.js engineer who owned a production microservice for transactional workflows in a React + microservices platform, integrating REST and Kafka event processing. Emphasizes operability and correctness (idempotency keys, exponential backoff retries, DLQs, centralized logging/metrics/alerts) plus strong API DX via versioning and Swagger/OpenAPI with improved error contracts based on developer feedback.”

“Backend/AI engineer who has shipped production LLM systems end-to-end, including an AI request-routing service (FastAPI + BART MNLI + OpenAI/Gemini) that improved accuracy ~25% after launch via eval-driven prompt/category iteration. Also built an enterprise document intelligence/RAG platform on Azure (Blob/SharePoint/Teams ingestion, OCR/NLP chunking, embeddings in Azure Cognitive Search) with PII guardrails (Presidio), confidence gating, and scalable event-driven pipelines handling millions of documents.”