Vetted Event-Driven Architecture Professionals

“Hands-on implementation-focused candidate with experience owning cloud deployments and putting LLM/RAG workflows into production. They stand out for combining customer-facing deployment ownership with practical AI systems work, including retrieval tuning, hallucination mitigation, production incident response, and document-processing pipelines for messy real-world inputs.”

Saumay Killa

Screened

Mid-level Full-Stack Engineer specializing in AI SaaS and FinTech

New York, NY3y exp

“Built a career platform feature end-to-end that generates tailored resumes and cover letters using a React/TypeScript frontend, Postgres, and AWS Lambda/SQS backend. Strong in event-driven, serverless architecture and pragmatic product iteration, with a quantified 60% improvement in onboarding completion after redesigning the UX with resume parsing and a multi-step flow.”

Tong Wu

Screened

Senior Software Engineer specializing in full-stack SaaS and cloud systems

Ontario, Canada8y exp

“Built and owned Laserfiche's Schedule Custom Report platform end-to-end, spanning Angular frontend, backend orchestration, and production observability for an enterprise reporting workflow. Stands out for integrating multiple independent microservices with RabbitMQ-based event orchestration while also improving UX on complex migration tooling.”

“Backend engineer with hands-on ownership of banking microservices from initial design to launch and production support, including security, CI/CD, observability, and incident response. Stands out for measurable modernization impact—~35% faster backend processing, ~40% lower query latency, and ~30% better deployment cycles—and for a pragmatic approach to both Kafka-based async systems and controlled LLM integration in enterprise workflows.”

“Built and deployed an AI-driven expense categorization workflow integrating OpenAI API and PGVector to automate general ledger coding. Stands out for combining LLM/embedding architecture with finance operations context, stakeholder-facing deployment ownership, and measurable impact of roughly 30%+ reduction in manual coding effort.”

“Built an internal RAG assistant for financial documents using FastAPI, OpenAI APIs, and vector search, improving document search speed and reducing manual effort for the business team. Stands out for a pragmatic approach to AI engineering: uses AI heavily for productivity, but keeps human judgment central and has designed retrieval, validation, and summarization workflows end-to-end.”

“Full-stack/product-minded engineer with strong React/TypeScript depth who has owned systems end-to-end, from UI architecture to backend services and data design. At Qualcomm, they built both a telemetry dashboard and an ML model drift monitoring platform for 20+ edge models, including post-launch tuning that cut false positives by 60%. They also demonstrate 0→1 startup execution by solo-building a production RAG document Q&A platform with JWT auth, Stripe gating, and sub-300ms retrieval.”

“Engineer working on high-throughput financial systems who uses AI pragmatically to accelerate development without sacrificing design ownership, correctness, or compliance. Particularly interesting for teams building regulated, real-time platforms: they have hands-on experience integrating fraud detection models into microservices, handling transaction ingestion, scoring, decisioning, and throughput-sensitive asynchronous workflows.”

“Currently building a DBC (Digital Birth Certificate) agentic AI system to speed root cause investigation for quality issues at their company. They bring hands-on experience designing and leading multi-agent workflows, including orchestrator/root-agent patterns, evaluation agents, clarification agents, and practical guardrails for hallucination, bias, and rate-limit management.”

“Backend engineer with experience evolving a high-volume agricultural loan processing platform (APMS) at HDFC Bank, emphasizing transactional integrity, auditability, and modularity while integrating with credit bureaus, document management, and risk engines. Also improved automation/reporting robustness at Trend Micro by catching duplicate-event retry edge cases and adding idempotency safeguards.”

“Frontend engineer focused on marketing and analytics products, including a real-time multi-touch attribution dashboard. Uses Next.js (SSR/ISR) with React/TypeScript and Tailwind, and emphasizes quality at scale via automated testing, CI/CD (GitHub Actions), feature-flagged staged rollouts, and Mixpanel-driven iteration. Experienced modern state management patterns (React Query + Zustand) and performance tuning (code-splitting, dynamic imports, lazy loading).”

“Full-stack engineer with experience at Vanguard, PNC, and Humana building customer-facing investment/banking flows and internal ops tools using Angular/React/TypeScript with Spring Boot microservices. Strong in shipping time-sensitive changes safely via automated testing/CI (JUnit/Mockito, Jenkins, SonarQube) and in operating event-driven microservices with Kafka (idempotency, retries, correlation IDs). Improved internal tool adoption by responding to ops/support feedback with query optimization and clearer search results.”

“Developer with experience across Drupal and Java/Spring Boot applications using React/jQuery for UI and API-driven features. Has handled production issues by tuning reverse proxy timeouts for login problems and troubleshooting data pipeline inaccuracies by fixing database queries, with a focus on performance and careful verification before changes.”

“Platform-minded JavaScript/TypeScript engineer who has maintained and evolved shared NPM-distributed libraries at Capital One and HCA Healthcare, treating internal packages like open source (issue triage, PR reviews, roadmap, docs). Known for methodical debugging and performance work—e.g., diagnosing latency spikes via load testing/instrumentation and redesigning middleware to avoid redundant parsing—paired with strong developer enablement through examples and migration notes.”

“Maintained and improved a set of JavaScript packages at JPMorgan, including a major refactor of an event-emission layer used in LLM streaming that delivered ~20% runtime speedup with no API changes. Known for a measurement-driven performance approach (profiling + simplification + validation), strong backward-compatibility discipline, and documentation that accelerates internal adoption and reduces support questions.”

“Backend engineer who built a containerized Flask service powering an engineering metrics dashboard by syncing GitHub and Jira data into PostgreSQL, with strong emphasis on schema design, query performance, caching, and background processing. Has hands-on experience with SaaS multi-tenancy (tenant scoping + Postgres RLS) and integrating AI/ML inference via separate model-serving services (FastAPI + TensorFlow Serving) and external APIs (OpenAI/Hugging Face/PyTorch).”

“Software engineer with Citi Bank experience building real-time fraud validation/scoring for loan processing, spanning Spring Boot microservices and a FastAPI Python service secured with OAuth2/JWT. Delivered React/TypeScript operations dashboards and deployed containerized services via Docker/Kubernetes with Jenkins CI/CD, while also tuning databases (Oracle/Postgres) and handling high-volume latency/scaling issues using ELK, caching, and autoscaling on AWS.”

“Cloud/Kubernetes-focused production engineer with experience running 99.95% uptime platforms across AWS/Azure/GCP. Strong in incident response and performance troubleshooting (including a 30% MTTR reduction), and in building secure CI/CD and Terraform-based IaC for AKS/GKE microservices with robust change controls and rollback practices. Notably does not have direct IBM Power/AIX/VIOS/HMC or PowerHA/HACMP ownership.”

“Backend-leaning product engineer with DevSecOps depth who has shipped real-time, Kafka-driven data pipelines and AI-enabled customer-facing features to production on AWS. Built a Spring Boot API layer serving real-time predictions at 100K+ requests/day, improving latency by 35% and user task completion by ~25%, and delivered a React/TypeScript dashboard plus a Postgres audit/history model optimized for search and large event volumes.”

“Data engineer focused on reliable, scalable analytics pipelines and external data collection. Has owned end-to-end pipelines processing 5–10M records/day, serving Snowflake data marts to Power BI/Tableau, and reports ~99% reliability through strong validation/monitoring. Also shipped versioned REST APIs for curated data with query optimization and caching.”

Chris Colinsky

Screened

Executive Technology Leader/CTO specializing in data platforms, AI agents, and e-commerce/payments

Los Angeles, CA23y exp

“Engineering leader with hands-on coding time who has driven major commerce and data-platform transformations: defined goop’s omnichannel strategy, unified payments to Square, and rebuilt real-time NetSuite inventory flows plus forecasting tools. Currently reorganized engineering into Product/Data/Support teams to hit aggressive seasonal roadmaps, and led a data-lake/medallion ELT refactor feeding embedded analytics (Tinybird) with improved reliability and cost efficiency; also accelerates onboarding via AI coding tools in a serverless, event-driven architecture.”

SNEHA KUSUMA

Screened

Mid-level Java Full-Stack Developer specializing in banking and telecom platforms

Dallas, TX5y exp

“Frontend-focused engineer with experience at T-Mobile and U.S. Bank who maintained a TypeScript utility library (types, tests, build pipeline, and docs) adopted by multiple teams, and improved React workflow performance by refactoring components and optimizing data fetching. Known for pragmatic cross-team support—reproducing issues quickly, shipping well-tested fixes, and managing changes carefully to avoid breaking downstream apps.”

Sanket Dumbare

Screened

Mid-Level Software Engineer specializing in cloud-native microservices and FinTech platforms

USA3y exp

“Backend/platform engineer who led an end-to-end Python (FastAPI) transaction analytics microservice for real-time financial monitoring, including SQS ingestion, scoring/aggregation, and low-latency APIs. Strong AWS + Kubernetes/GitOps background (EKS, ArgoCD, Jenkins, ECS/ECR, CloudWatch) with hands-on experience scaling event-driven systems and executing phased on-prem to AWS migrations.”

Deeresh Gajjala

Screened

Senior Software Engineer specializing in Java/Spring Boot microservices and AWS payments systems

Dallas, TX6y exp

“Senior software engineer with Amazon experience who owned end-to-end improvements to a real-time payment authorization service, rebuilding it as a reactive Spring WebFlux microservice with saga orchestration and Kafka event streaming, deployed on AWS EKS with strong observability. Also built React+TypeScript and Node/Express full-stack workflow apps (onboarding, campaign management, admin review) and has experience shipping quickly in ambiguous startup environments while maintaining reliability and data correctness.”