Vetted GraphQL Professionals

Pre-screened and vetted.

EK

Executive Engineering & Product Leader specializing in digital commerce, customer platforms, and applied AI

Oceanside, CA25y exp
Ingram MicroUniversity of Rochester
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SM

Senior Full-Stack Engineer specializing in Unity/C# and AI-driven VR/mobile healthcare systems

Cleveland, TN14y exp
Avegen HealthITT Technical Institute
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XJ

Senior Software Engineer specializing in FinTech backend systems

Kirkland, WA8y exp
SoFiNortheastern University
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OS

Senior Software Engineer specializing in healthcare IT and EHR interoperability

Burlingame, CA11y exp
Epic SystemsMIT
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DC

Senior Full-Stack Engineer specializing in healthcare, cloud, real estate, and FinTech

Lynn Haven, FL12y exp
CurativeUniversity of South Florida
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SZ

Mid-level Full-Stack Engineer specializing in consumer web platforms

Los Angeles, CA5y exp
Chuwa AmericaUniversity of Pennsylvania
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KC

Staff Software Engineer specializing in Healthcare SaaS and real-time systems

Seattle, WA11y exp
AmazonMonash University
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QG

Staff Software Engineer specializing in FinTech and scalable distributed systems

Menlo Park, CA12y exp
RobinhoodAugusta University
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HT

Senior Full-Stack Software Engineer specializing in large-scale streaming platforms

Seattle, WA10y exp
DisneyNYU
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WW

Senior AI Engineer specializing in machine learning, NLP, and generative AI

Madison, WI13y exp
AmazonCase Western Reserve University
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DC

Senior Software Engineer specializing in AI backend platforms and FinTech systems

Hoboken, NJ11y exp
DoorDashOhio State University
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YH

Senior Product Designer specializing in AI, enterprise UX, and cloud platforms

9y exp
CloudflareUniversity of Pennsylvania
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RJ

Executive technology leader specializing in cloud platforms, AI, and enterprise architecture

30y exp
Smackz
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KD

Kanaad Deshpande

Screened ReferencesStrong rec.

Intern Software Engineer specializing in distributed systems and cloud infrastructure

San Francisco, CA1y exp
Sigma ComputingUC San Diego

Built and operated a production warehouse metadata collection platform at Sigma Computing, integrating Go/gRPC services with a TypeScript backend and MySQL, with strong emphasis on idempotency, retries, bounded-concurrency job queues, and Datadog-based observability. Also created Kurral (kurral.com), an AI agent runtime security and observability/governance SDK/proxy concept, iterating via pilot-customer feedback and market research; targeting founding engineer roles with $180–200k base and ~2–5% equity.

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AS

Akshat Shah

Screened ReferencesStrong rec.

Entry-level Software Engineer specializing in full-stack and AI systems

Los Angeles, CA1y exp
Integrated Media Systems CenterUSC

Frontend-leaning full-stack engineer who described owning an artist search and detail experience across UI, backend integrations, and data modeling. They show practical strength in scalable React architecture, TypeScript safety, and performance tuning, with a product-minded approach to shipping 0→1 features quickly and iterating after launch.

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Manaswini Gogineni - Mid-Level Software Engineer specializing in cloud infrastructure and full-stack web development in San Francisco, CA

Manaswini Gogineni

Screened ReferencesStrong rec.

Mid-Level Software Engineer specializing in cloud infrastructure and full-stack web development

San Francisco, CA2y exp
CiscoUniversity of Wisconsin–Madison

Backend engineer at Electric Hydrogen who built a serverless device-log ingestion and processing platform in Python/Flask, scaling throughput (4x peak ingestion) while keeping sub-300ms API latency. Strong in Postgres/SQLAlchemy performance (partitioning, materialized views) and production ML integration (ONNX model served via FastAPI microservice with async batch inference, Redis feature caching, and drift monitoring via S3/Lambda). Experienced designing secure multi-tenant systems with schema-per-tenant isolation and KMS-backed encryption.

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BS

Engineering Manager specializing in AI/ML platforms and 0→1 product delivery

Cambridge, MA15y exp
ElsevierHarvard University

Player-coach engineer/lead on a high-scale research integrity platform ("Lighthouse") that flags fraud/manipulation signals across ~3M academic manuscripts per year. Owns architecture decisions (ADRs), implements across Go/Java/React services, and introduced NLP (SciBERT embeddings + human-in-the-loop) to assess out-of-context citations while also handling production incidents with a data-consistency-first approach.

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Rashi Agrawal - Mid-Level Full-Stack Software Engineer specializing in distributed systems and cloud-native microservices in Novi, MI

Rashi Agrawal

Screened

Mid-Level Full-Stack Software Engineer specializing in distributed systems and cloud-native microservices

Novi, MI4y exp
GenthermUniversity of Pennsylvania

Backend engineer (4 years) who built an end-to-end Python backend for a patent-pending in-car massager/heater system, including GraphQL data modeling and Bluetooth integration with an ESP32 microcontroller (reverse engineered a niche protocol). Also has strong platform experience: on-prem Kubernetes/CI-CD (Jenkins/GitLab, exploring ArgoCD GitOps), Terraform-based infra workflows, a RabbitMQ messaging library used across microservices, and an on-prem migration of ~30 critical applications with rollback/parallel-run strategy.

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EC

Edmund Chan

Screened

Mid-level Frontend Engineer specializing in web platforms and internationalization

New York, NY4y exp
BloombergUniversity of British Columbia

Frontend engineer with significant ownership of Bloomberg's Japanese regional platform, building a complex multi-app Next.js experience for retail investors and financial professionals. Stands out for combining high-scale localization architecture, advanced TypeScript/component-system design, and measurable UX performance wins in demanding financial products.

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Arun Ganesh - Junior Software Engineer specializing in healthcare AI and cloud infrastructure in San Francisco, CA

Arun Ganesh

Screened

Junior Software Engineer specializing in healthcare AI and cloud infrastructure

San Francisco, CA3y exp
AmazonCal Poly San Luis Obispo

Amazon Health AI engineer who has owned both full-stack clinical product features and production LLM systems end to end. Built HIPAA-compliant GraphQL and agentic RAG architectures for provider workflows across 125,000+ patients, with measurable impact including 30% higher clinical relevance, 55% lower lookup time, and 12% less false medical information.

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SL

Sam Liao

Screened

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

Philadelphia, PA3y exp
VanguardCarnegie Mellon University

Full-stack engineer at Vanguard who architected and shipped a production AI onboarding chatbot using React, Python, LangChain, RAG, and AWS Bedrock, reaching 50,000+ prospects in two months and reducing drop-off by 26%. Particularly compelling for teams building regulated AI products: they combine hands-on full-stack delivery with guardrails, observability, and experimentation, and also build consumer AI products on the side in endurance coaching.

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Shailaja Domala - Executive product and AI leader specializing in data platforms and analytics in California, USA

Executive product and AI leader specializing in data platforms and analytics

California, USA24y exp
CerenityCornell University

Engineering leader with deep experience at Visa building and modernizing large-scale analytics platforms, including refactoring legacy systems into globally available microservices on AWS. Combines hands-on technical judgment in architecture, search platform evaluation, and service reliability with management of distributed international engineering and data teams.

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CN

Executive Chief of Staff and Strategic Operations Leader across SaaS, government, and national security

Wayland, MA20y exp
DatasiteMIT Sloan School of Management

Entrepreneurial consultant who relocated to Boston to build a practice from scratch through intensive networking and pro-bono work, leading to being listed as a trusted provider in Leader Bank's CEO toolbox and generating qualified leads. Uses structured strategic frameworks (OODA, Porter's Five Forces, SWOT) to evaluate risk, resource lift, and enterprise/customer impact, with a strong ownership-and-accountability orientation.

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