Vetted GraphQL Professionals

Pre-screened and vetted.

SK

Mid-level Software Engineer specializing in distributed systems and full-stack development

Sunnyvale, CA5y exp
AmazonStony Brook University
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NC

Mid-level Full-Stack Engineer specializing in scalable web platforms and AI/ML tooling

San Francisco, CA6y exp
Scale EvaluationUniversity of Cincinnati
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VB

Mid-level Software Developer specializing in full-stack platforms for mobility, travel, and logistics

Cleveland, OH5y exp
UberYoungstown State University
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RC

Senior Front-End/Full-Stack Engineer specializing in cloud-native SaaS and enterprise web apps

11y exp
NorthStandard
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JH

Executive Engineering Leader (CTO/VP) specializing in platform scaling and video streaming

Los Angeles, CA21y exp
TrueParity
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CS

Senior Full-Stack Java Developer specializing in cloud-native microservices

7y exp
Goldman Sachs
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WH

Senior AI & Systems Architect specializing in ML infrastructure and FinTech

Allentown, PA7y exp
Amazon
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VM

Vinosh Mathuranayagam

Screened ReferencesStrong rec.

Senior solutions architect specializing in digital health and healthcare IT

Remote, United States10y exp
Yo-Vivo HealthJohns Hopkins University

Healthcare solutions architect with roughly 7 years at Mass General Brigham, evolving from application specialist to broad cross-functional architect supporting telehealth, digital health, conversational AI, generative AI, and legal workflow initiatives. Particularly strong at translating complex clinical and business problems into enterprise architectures, integrations, and stakeholder-specific demos across hospital leadership, clinicians, IT, and vendors.

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RE

Robert Elwell

Screened

Executive Engineering Leader specializing in cloud platforms, DevOps, and security

18y exp
MacStadiumUniversity of Texas at Austin

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.

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AS

Arnav Singh

Screened

Junior Software Engineer specializing in full-stack web, cloud data, and applied ML

Hanover, NH2y exp
PlayStationDartmouth College

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).

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SG

Sanskar Gupta

Screened

Mid-level Full-Stack Developer specializing in Java/Spring Boot, React, and cloud microservices

KS, USA4y exp
DeloitteWichita State University

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.

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NK

Engineering Manager specializing in mobile monetization and consumer apps

Bay Area, CA13y exp
GrindrIllinois Institute of Technology

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.

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Surya Teja - Mid-level Backend/Full-Stack Engineer specializing in AI and FinTech payments in Tempe, AZ

Surya Teja

Screened

Mid-level Backend/Full-Stack Engineer specializing in AI and FinTech payments

Tempe, AZ4y exp
StripeArizona State University

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.

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Sourabh Jain - Director of Software Engineering specializing in enterprise Data, ML & AI platforms in Bay Area, CA

Sourabh Jain

Screened

Director of Software Engineering specializing in enterprise Data, ML & AI platforms

Bay Area, CA23y exp
RSA SecurityShri G. S. Institute of Technology and Science

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.

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Paul Liu - Senior Software Engineer specializing in cloud-native backend and web/mobile apps in Seattle, WA

Paul Liu

Screened

Senior Software Engineer specializing in cloud-native backend and web/mobile apps

Seattle, WA8y exp
TeslaUniversity of Calgary

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.

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JY

Jay Yepuri

Screened

Mid-level Software Engineer specializing in AWS backend and cloud infrastructure

Seattle, WA4y exp
AmazonIndiana University Bloomington

Full-stack engineer with AWS Skill Builder experience building internal content-management and search workflows in TypeScript across React and Node.js. They drove a shift from keyword to semantic search using OpenSearch and Bedrock Titan Embeddings, delivering a 5x reduction in discovery time while also improving production reliability and observability for large-scale content workflows.

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HG

HARSHA GADDAM

Screened

Mid-level Full-Stack Java Developer specializing in cloud microservices

Chicago, IL5y exp
NVIDIAIllinois Institute of Technology

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.

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Jenya Rusinova - Mid-level Frontend Engineer specializing in cloud enterprise applications in East Palo Alto, CA

Mid-level Frontend Engineer specializing in cloud enterprise applications

East Palo Alto, CA3y exp
Amazon Web ServicesSaint Petersburg State University of Economics

Frontend-focused product engineer with experience owning production launches in observability/monitoring, including extending an existing web-only service to support mobile users without disrupting current customers. Stands out for balancing speed and safety through feature flags, regional beta rollouts, bug bashes, and close collaboration with PM, design, and backend teams in ambiguous environments.

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BS

Mid-level Full-Stack Developer specializing in cloud-native backend services and real-time data platforms

Remote, USA4y exp
NetflixUniversity of Dayton

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.

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BK

Mid-level Full-Stack Software Engineer specializing in cloud microservices and AI integration

Jersey City, NJ3y exp
UberPace University

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.

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PY

Mid-level Software Development Engineer specializing in AWS telemetry and DDoS mitigation

Seattle, WA3y exp
Amazon Web ServicesTexas A&M University-Commerce

Amazon engineer who built an Amazon Bedrock-powered summarization layer over large-scale network/service telemetry (“top talker” insights) to help security engineers triage anomalies faster. Emphasizes production-grade design patterns for LLM features—non-blocking enrichment, deterministic fallbacks, strict structured outputs, and monitoring to preserve trust in source-of-truth telemetry.

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Likhitha Bethi - Mid-level Software Engineer specializing in backend systems, distributed systems, and applied AI in Stony Brook, NY

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

Stony Brook, NY4y exp
Stony Brook UniversityStony Brook University

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.

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