Vetted Engineering Professionals in the Greater Seattle

Pre-screened and vetted in the Greater Seattle.

PJ

Po Jui Lin

Screened

Mid-Level Full-Stack Engineer specializing in cloud platforms, cybersecurity web apps, and IoT

Seattle, WA3y exp
AmazonUniversity of Washington

Backend engineer with experience at Amazon building an API-driven service (APS) for large-scale prompt optimization jobs using AWS Step Functions, Batch/Fargate, DynamoDB, and S3, emphasizing idempotency, observability, and secure execution boundaries. Also led a multi-tenant enterprise policy/configuration backend refactor at MAMIT Cyber with versioned schemas, shadow writes, feature-flagged rollout, and PostgreSQL RLS-based tenant isolation.

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Chetan Mukhopadhyay - Senior Engineering Manager specializing in software quality, automation, and web/mobile platforms in Seattle, WA

Senior Engineering Manager specializing in software quality, automation, and web/mobile platforms

Seattle, WA16y exp
BayerCal State Long Beach

Engineering leader at Bayer Crop Science leading a Core Platform team responsible for widely used open-source TypeScript/React and mobile SDKs (npm/GitHub) embedded across 10M+ monthly active devices. Known for shipping high-performance, backward-compatible developer frameworks with rigorous release discipline (bi-weekly releases, 99.99% uptime, long streaks of zero breaking changes) and major DX wins (onboarding cut to minutes, support tickets down 82%).

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JW

Senior QA/Test Architect specializing in accessibility and test management

Redmond, WA18y exp
SogetiUniversity of Phoenix
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Sakshi Jagani - Junior Software Development Engineer specializing in web UI and AI-enabled experiences in Seattle, WA

Junior Software Development Engineer specializing in web UI and AI-enabled experiences

Seattle, WA1y exp
AmazonUniversity of Texas at Dallas
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HC

Junior Software Engineer specializing in cloud platforms and backend security

Seattle, WA1y exp
AmazonNorth Carolina State University
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AL

Senior Full-Stack & AI Engineer specializing in scalable ML systems

Seattle, WA11y exp
Evertune AIUniversity of Illinois Chicago
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YW

Mid-level Software Engineer specializing in Python, cloud tooling, and NLP/RAG systems

Seattle, WA3y exp
Amazon Web ServicesGeorgia Tech
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PG

Mid-Level Software Engineer specializing in distributed backend systems and event-driven architecture

Seattle, WA4y exp
GEICOUniversity at Buffalo
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TT

Senior QA Test Engineer specializing in automation and AR/VR testing

Bellevue, WA10y exp
MetaYear Up
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JM

Senior Software Engineer specializing in front-end cloud and web platforms

Bellevue, WA8y exp
SnapUniversity of Alabama in Huntsville
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LB

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

Bellevue, WA5y exp
AmazonMissouri State University
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SP

Mid-Level Software Engineer specializing in Cloud-Native Platforms on AWS and Kubernetes

Seattle, WA5y exp
AmazonUniversity at Buffalo
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US

Mid-level Software Engineer specializing in AI/ML and AWS cloud platforms

Bellevue, WA3y exp
AmazonNortheastern University
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SS

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

Seattle, WA6y exp
UberUniversity of Texas at Arlington
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KV

Senior Software Engineer specializing in distributed systems and cloud-native microservices

Seattle, WA5y exp
AmazonUniversity of Central Missouri
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SK

Mid-level Software Engineer specializing in distributed systems and data platforms

Seattle, WA7y exp
NordstromNYU
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AM

Mid-level Full-Stack Developer specializing in microservices and AWS DevOps

Seattle, WA5y exp
JPMorgan ChaseCleveland State University
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AR

Mid-Level Software Engineer specializing in cloud-native distributed systems

Seattle, WA6y exp
Mercedes-BenzRochester Institute of Technology
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DV

Senior Software Engineer specializing in cloud backend systems and LLM-powered agents

Seattle, WA5y exp
AmazonSan José State University

Amazon Fire TV Devices engineer who built and shipped a production LLM-powered lab triage and validation system that grounds recommendations in internal runbooks/known-issue data and pushes evidence-based actions via dashboards and Slack. Emphasizes safety and measurability with structured JSON outputs, replay-based evaluation on historical incidents, and production metrics (e.g., disagreement rate and time-to-first-action), plus cost/latency optimizations like caching, batching, and rule-based fast paths.

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