Vetted Amazon EKS Professionals

Pre-screened and vetted.

SM

Mid-level Data Engineer specializing in AI/ML data platforms and real-time streaming

Arkansas, USA6y exp
WalmartUniversity of Central Missouri
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SM

Mid-level Data Engineer specializing in cloud lakehouse and streaming pipelines

California, USA5y exp
JPMorgan ChaseCalifornia State University, Fullerton
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SL

Senior Full-Stack Engineer specializing in cloud microservices on AWS

6y exp
AmazonUniversity of Missouri-Kansas City
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MN

Senior DevOps Engineer / AWS Solutions Architect specializing in Kubernetes and DevSecOps

New York, NY7y exp
UberKabul University
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VN

Mid-level AI Engineer specializing in ML, MLOps, and enterprise NLP

5y exp
Goldman SachsUniversity of Connecticut
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AF

Principal AI/ML Engineer specializing in LLM and NLP platforms

Tampa, FL11y exp
RivianFlorida State University
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YO

Senior AI Platform Engineer specializing in agentic AI and RAG systems

Alpharetta, GA7y exp
Morgan StanleyKakatiya Institute of Technology and Science
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NS

Senior Software Engineer specializing in cloud platforms and distributed systems

Nashville, TN5y exp
OracleSanta Clara University
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VN

Mid-level Software Engineer specializing in FinTech platforms

USA4y exp
CitigroupUniversity at Buffalo
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HS

Senior Full-Stack Engineer specializing in Java microservices and FinTech

San Francisco, CA5y exp
AtlassianUniversity of the Cumberlands
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KP

Senior Full-Stack Engineer specializing in AI, FinTech, and Healthcare IT

Tyler, TX10y exp
BrightOpsJones College
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KR

Mid-level Software Developer specializing in backend cloud and API platforms

California, USA3y exp
UberNew York Institute of Technology
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SS

Executive CTO/VP Engineering specializing in high-performance AI, data systems, and distributed infrastructure

Vancouver, Canada20y exp
Clustera
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JA

Senior Software Engineer specializing in distributed systems, IoT, payments, and blockchain

Chicago, IL13y exp
Moen
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LX

Longyang Xu

Screened ReferencesStrong rec.

Junior Full-Stack Software Engineer specializing in cloud microservices and ML-driven products

Quincy, MA1y exp
GraniteCarnegie Mellon University

Backend engineer with hands-on ownership of Python/Flask microservices and recommendation systems across edtech and telecom. Deployed and operated real-time personalization/recommendation platforms on AWS EKS with Jenkins-based CI/CD, GitOps-style declarative configs, and strong observability practices. Has migration experience moving legacy mixed environments to modern containerized Kubernetes and built Kafka pipelines feeding ML services while managing schema evolution.

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MM

Senior Software Engineer specializing in AI/ML backend and cloud infrastructure

Bentonville, AR11y exp
WalmartUniversity of Houston

Backend/data platform engineer with production experience at Walmart and Molina Healthcare, building Python microservices on AWS (EKS + Lambda) for real-time inventory and recommendation systems. Strong in reliability/observability and incident leadership, plus modernizing legacy healthcare workflows and building resilient AWS Glue/PySpark pipelines with schema evolution and data quality controls.

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VB

Intern AI/ML Engineer specializing in LLM applications and data infrastructure

Redmond, Washington, USA3y exp
UberUniversity of Memphis

Hands-on LLM practitioner who built a production document-processing pipeline in Python, tackling long-document handling and latency with chunking/batching and a user-driven correction feedback loop. Experienced operationalizing AI workflows with Kubernetes (CronJobs, autoscaling, scheduled data cleaning and weekly retraining) and applying structured testing/evaluation (E2E, LLM-as-judge, HITL) while communicating solutions clearly to non-technical clients using visual diagrams.

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Daniel Jeong - Junior Full-Stack Engineer specializing in real-time platforms and AI tools in Cambridge, MA

Daniel Jeong

Screened

Junior Full-Stack Engineer specializing in real-time platforms and AI tools

Cambridge, MA3y exp
DraperColgate University

Early-career full-stack engineer with unusual depth in mission-critical environments: helped build a cybersecurity operations platform from scratch as the third engineer and shipped it to the National Election Commission of South Korea. Also worked on defense-focused situational awareness software, combining React/WebGL frontend performance work with backend data transformation for real-time weather and map overlays.

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OO

Senior DevOps/DevSecOps Engineer specializing in AWS & Azure cloud infrastructure

Fairfax, VA10y exp
Technatomy Digital SolutionUniversity of Lagos

Infrastructure/DevOps-focused engineer working across Linux-based enterprise platforms that include IBM Power/AIX in a broader OpenShift/Kubernetes and cloud ecosystem. Built Azure DevOps CI/CD for containerized deployments and resolved a production deployment failure by tracing ImagePullBackOff to outdated registry credentials in Kubernetes secrets. Uses Terraform (with modular structure) plus Ansible to provision and standardize production environments with pipeline-based validation.

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MM

Principal Applied Scientist specializing in ML systems and Generative AI

Tampa, FL11y exp
OracleUniversity of South Florida

Built and owned an end-to-end agentic RAG chatbot platform for Baptist Health that helped clinicians access policy and clinical documents faster, reducing manual lookup by 80% and delivering about $2M in annual savings. Brings strong healthcare GenAI production experience, including HIPAA-aligned governance, PHI redaction, observability, evaluation, and scalable Python/Kubernetes deployment practices.

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MN

mahesh narne

Screened

Senior Full-Stack Software Engineer specializing in cloud-native microservices and web apps

San Jose, CA3y exp
PayPalUniversity of Central Missouri

Backend-focused engineer building customer support/order-tracking platforms with Java 17/Spring Boot microservices and a React/TypeScript frontend. Deep experience running event-driven systems on Kubernetes (Kafka, Redis, MySQL) with strong observability (Prometheus/Grafana/Splunk), SLOs, and safe deployment practices (feature flags, canaries). Also built an internal monitoring/debugging dashboard that consolidated metrics and logs for on-call engineers and was adopted by other teams to speed incident response.

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