Vetted GraphQL Professionals

“Senior engineering/CTO-level leader with hands-on delivery of serverless, event-driven cloud governance platforms (deployed across multiple GE business units) and experience building adaptable usage-based billing at UserTesting. Has advised startups (including CaseText during YC) and supported fundraising and acquisition due diligence, including investor materials for a smart cooler custody management system presented to BARDA during Operation Warp Speed.”

“Full-stack engineer who has owned an operational reporting/dashboard product end-to-end—building a React UI, designing/implementing FastAPI services, and deploying/operating on AWS. Demonstrates strong performance engineering (Postgres query/index tuning using EXPLAIN ANALYZE) with concrete impact (reports reduced from tens of seconds to a few seconds) and a reliability mindset across observability, migrations, and resilient third-party/ETL integrations.”

“Backend engineer who evolved the X-Ray gaming analytics platform, leading a zero-downtime MongoDB→AWS DocumentDB migration with dual-write, checksum-based validation, and Kubernetes canary rollouts while maintaining real-time monitoring for millions of concurrent sessions. Strong in FastAPI/Python API scaling and performance tuning (cut latency from ~2s to <150ms and reduced DB load 90%) plus production-grade auth/RLS security patterns (JWT, Supabase Auth, PostgreSQL RLS).”

“Backend engineer with Tesla experience building Python-based, serverless microservices for a supply chain portal, including a MongoDB-backed tracking/logging system and a reconciler Lambda to manage retries and failures. Has hands-on Kubernetes (EKS) and GitOps (Argo CD) experience, plus real-time Kafka pipelines for fleet/IoT telemetry and proxy-based migrations from monolith systems to AWS databases.”

“Backend engineer with hands-on experience building Python/Flask microservices using PostgreSQL/SQLAlchemy, JWT auth, Docker, and GitHub Actions CI/CD. Strong in performance and scalability work—migrated heavy processing to Celery/Redis, tuned queries with EXPLAIN ANALYZE and indexing, and delivered 50%+ API latency reduction. Also integrates AI workflows (OpenAI APIs) with batching/caching/fallbacks and has implemented multi-tenant data isolation patterns.”

“Former Walmart Director of Software Engineering who left in March 2025 to build products for clients. Recently delivered an LLM/RAG-based UNSPSC classification solution for an MRO client using a multi-stage retrieval + web search + prompt-engineering workflow, and has led large-scale retail forecasting initiatives and high-severity cloud-migration incidents end-to-end.”

“Engineering Manager/Tech Lead on Grindr’s monetization team who helped ship an AI-powered conversation summary feature (A-list), contributing across Android freemium implementation and backend LLM workflow service architecture/reviews. Demonstrated strong operational ownership by leading a Boost production incident from detection through rollback and prevention, and improved team throughput by introducing a lightweight end-to-end delivery process in a high-growth environment.”

“Stripe engineer who shipped an end-to-end merchant fraud insights dashboard, spanning Spring Boot/Kafka risk-scoring services and a React+TypeScript UI. Focused on low-latency, high-volume transaction processing and production operations on AWS (EKS/CloudWatch), including handling a real traffic-spike latency incident via query optimization, indexing, and rate limiting.”

“Backend/data engineering candidate with Netflix experience designing and migrating analytics platforms from batch to real-time streaming (Kafka/Flink) across AWS and GCP. Delivered measurable improvements (40% lower data delay, 99.9% accuracy) using phased rollouts, automated data validation (Great Expectations), and strong observability (Prometheus/Grafana), and proactively hardened pipelines with idempotency to prevent duplicate Kafka processing.”

“Backend/distributed-systems engineer with Uber experience building real-time telemetry and safety signal pipelines. Strong in Kafka-based event-driven architectures, low-latency processing under peak load, and production reliability via monitoring, retries, and fallback logic; has Docker/Kubernetes and CI/CD deployment experience.”

“Goldman Sachs engineer who owned end-to-end features for an internal onboarding and case management platform, spanning React/TypeScript UI, a GraphQL gateway, and Node + Spring WebFlux microservices. Built and operated a Kafka-based ingestion and search pipeline with DLQs, retries, idempotency, and strong observability, and improved developer experience via backward-compatible GraphQL API design and schema-driven documentation.”

“Backend/data engineer with hands-on production AWS experience spanning serverless APIs (Chalice/Lambda/API Gateway/Cognito) and data pipelines (Glue PySpark + Step Functions). Has modernized a legacy SAS reporting system into AWS microservices and implemented schema-drift detection and incident prevention for ETL workflows, plus measurable SQL tuning wins (30 min to <10 min runtime).”

“Internship experience at Intuit building an LLM-grounded QA system for internal microservice data across 100+ microservices, using a graph database approach (evaluated Neo4j and selected AWS Neptune for production alignment). Also has UC Berkeley research experience (including work with Prof. Dawn Song / Berkeley Eye Research Lab) and cross-functional collaboration with bioinformatics/biology teams to deploy software systems on research servers.”

“Backend engineer with experience at Meta and Accenture building regulated-data systems (healthcare/financial) using Python/Flask and Postgres. Has scaled high-throughput services to millions of daily requests, delivering measurable latency wins (~40% API latency reduction; ~35% faster DB-backed endpoints), and has productionized ML inference services using Docker/Kubernetes and AWS (ECS/SageMaker).”

“Series C (Sigma Computing) full-stack engineer/intern who shipped production features across React/TypeScript and GraphQL, including a Recents/workbook activity reliability improvement that handled unsaved “exploration” events via deterministic backend updates. Emphasizes production quality through Jest/Cypress coverage and feature-flagged staged rollouts, and is recognized for UX-focused improvements (fast, accurate filtering at scale) and proactive cross-functional ownership.”

“Backend/platform engineer with hands-on ownership of Python services (Postgres/Redis/Celery) and measurable performance gains (~20–25%). Strong Kubernetes + ArgoCD GitOps experience delivering zero-downtime rollouts, plus led key reliability fixes (readiness probes, immutable tagging) and supported an on-prem to AWS migration using CDC replication and ALB traffic shifting; also built Kafka real-time analytics pipelines with schema registry.”

“Backend engineer with healthcare platform experience at Thirty Madison, combining Django for secure, data-heavy core services with FastAPI async microservices for real-time patient monitoring. Led Kubernetes migration with Istio service mesh, autoscaling (HPA), and stateful storage patterns, and implemented GitOps CI/CD using ArgoCD. Also built real-time Kafka streaming pipelines with reliability patterns like idempotent producers and offset management.”