Vetted Amazon API Gateway Professionals

Pre-screened and vetted.

NR

Senior Software Engineer specializing in distributed systems and cloud platforms

Remote8y exp
MicrosoftNortheastern University
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SM

Senior Software Engineer specializing in full-stack, cloud, and Generative AI

Seattle, WA10y exp
AmazonArizona State University
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JA

Senior Full-Stack Engineer specializing in Python and AWS serverless systems

Ingram, United States14y exp
Kaya AITexas State University
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EB

Senior Backend/Platform Engineer specializing in AWS-native data processing systems

Austin, TX11y exp
CiscoUniversity of Texas at Austin
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CB

Senior Staff Full-Stack Engineer specializing in AI copilots and cloud platforms

Cypress, Texas10y exp
RidgelineUniversity of Texas at Austin
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AB

Mid-level AI/ML Engineer specializing in LLMs and MLOps

5y exp
GoogleUniversity of North Texas
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NN

Mid-level Full-Stack Java Developer specializing in cloud and healthcare systems

4y exp
AmazonGeorge Mason University
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TP

Senior Full-Stack Engineer specializing in cloud-native enterprise and AI platforms

Hurdle Mills, NC11y exp
Tryon Creek SoftwareNorth Carolina State University
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PY

Senior Full-Stack Python Developer specializing in cloud, data platforms, and GenAI

Cupertino, CA12y exp
AppleUniversity of Phoenix
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SE

Staff AI & Data Engineer specializing in LLM systems and real-time data platforms

Salt Lake City, UT10y exp
Jump AILouisiana Tech University
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RP

Mid-level Full-Stack Software Engineer specializing in AI-powered applications

Seattle, WA5y exp
AmazonUniversity at Buffalo
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CS

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

7y exp
Goldman Sachs
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EP

Ethan Pribble

Screened ReferencesStrong rec.

Senior Software Engineer specializing in cloud cost intelligence and FinOps platforms

21y exp
CloudZeroNorthwestern University

Backend/data engineer with strong authorization and compliance-domain experience: led a phased migration from a simplistic role model to modern RBAC on a Python serverless stack (Auth0 + AWS Lambda/API Gateway), coordinating changes across 5 repos with extensive manual and automated validation. Previously built and operated custom ETL pipelines (Airflow + Groovy/Java on Spark/YARN/Hadoop) to normalize messy customer email/chat/voice data for NLP-driven financial compliance indicators, including complex email journaling metadata enrichment and large-scale remediation reprocessing after production bugs.

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JK

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

Seattle, WA4y exp
AmazonSaint Louis University

Engineer with hands-on experience across backend, full-stack, cloud, and AI/ML systems, with particular depth in Python, FastAPI, AWS Bedrock, SageMaker, and RAG-based architectures. Stands out for treating AI and agents as accelerators within disciplined production engineering, emphasizing guardrails, observability, latency/cost monitoring, and scalable system design.

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TW

Tianyi Wang

Screened

Entry-Level Backend/Cloud Engineer specializing in distributed systems and AI platforms

Seattle, WA1y exp
AmazonUniversity of Michigan

Full-stack engineer with deep serverless AWS experience who built VidToNote, an AI video analysis platform, end-to-end using Next.js App Router/TypeScript and an event-driven pipeline (API Gateway, Lambda, DynamoDB, S3, Step Functions, SQS). Strong on production reliability and observability (CloudWatch, X-Ray, structured logging), plus data/analytics work in Postgres with measurable query optimizations and durable LLM evaluation workflows. Amazon background; integrated 22 AWS services and completed AWS Solutions Architect Professional certification within a month.

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XL

Xicheng Liang

Screened

Intern AI/Full-Stack Engineer specializing in backend systems and applied machine learning

Chicago, IL1y exp
Becker’s HealthcareUniversity of Pennsylvania

Built and shipped a production agentic RAG system for healthcare analysts that automated compliance/operations knowledge retrieval across PDFs, reports, and databases. Emphasizes production reliability (monitoring, retries, fallbacks, async queues), strong evaluation/iteration loops, and measurable impact (3–10s responses and ~98% top-k retrieval accuracy).

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DB

Staff Software Engineer specializing in Healthcare platforms and AI data pipelines

Remote10y exp
DrwellBinghamton University

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).

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KARTHIKBABU VADLOORI - Mid-level Full-Stack Developer specializing in Spring Boot, React, and cloud microservices in San Francisco, CA

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

San Francisco, CA5y exp
MetaUniversity of Texas at Arlington

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).

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CK

Senior Software Engineer specializing in Python, cloud platforms, and distributed systems

Nashville, TN13y exp
i3 VerticalsUniversity of Chicago

Backend/data engineer with production experience at Walmart and HealthSnap building Python services and data pipelines on AWS (EKS, Lambda, Glue, Airflow). Strong reliability and operations focus—implemented idempotency + circuit breakers for peak-traffic consistency issues, GitOps CI/CD, and observability. Demonstrated measurable performance wins (Postgres p95 45s to <5s, ~60% CPU reduction) and modernized SAS batch workflows to Python with parallel-run parity validation and feature-flagged rollout.

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Daksh Jain - Mid-Level Software Development Engineer specializing in AWS streaming media platforms in Portland, OR

Daksh Jain

Screened

Mid-Level Software Development Engineer specializing in AWS streaming media platforms

Portland, OR3y exp
AmazonUC Davis

Full-stack engineer with hands-on Next.js App Router + TypeScript experience (built a RateMyProfessor-style platform end-to-end using RSC, dynamic routing, debounced search, and cache invalidation). Also has AWS backend depth—built a Step Functions-based wave rollout/feature access control framework for MediaPackage V2 with idempotency, retries, rollback, and ongoing correctness reconciliation.

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NH

Mid-level Full-Stack Engineer specializing in cloud-native data and enterprise platforms

USA5y exp
AmazonUniversity of Cincinnati

Software engineer with practical, day-to-day experience embedding AI into development workflows across coding, testing, code review, and AWS data pipelines. Uses tools like Claude, Cline, JUnit, Mockito, and Amazon Bedrock, and stands out for having a realistic, mature view of agent limitations, hallucinations, and the need for strong prompting and human validation.

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Kevin West - Executive engineering leader specializing in AI, cloud architecture, and startup product delivery in Phoenix, AZ

Kevin West

Screened

Executive engineering leader specializing in AI, cloud architecture, and startup product delivery

Phoenix, AZ15y exp
GoldenhourCarnegie Mellon University

Founding/backend engineering leader who built an AI product for car enthusiasts, recruited and managed cross-functional/offshore teams, and helped drive an $8M Series A after scaling a viral launch of 40k+ users in a weekend. Also built a sophisticated human-in-the-loop AI brand platform with agent orchestration and led a major AWS Step Functions migration that reduced platform costs from $30k/month to roughly $900/month.

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KI

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

Cupertino, CA5y exp
AppleCalifornia State University

Built internal banking operations products spanning full-stack dashboards and AI-assisted workflow tools. Shipped a RAG-based assistant using PostgreSQL/Redis retrieval with OpenAI and Claude APIs, and used audit-log measurement plus evals/traces to drive a reported ~30% reduction in manual review time.

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