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Vetted Java Professionals

Pre-screened and vetted.

KS

Senior Applications Engineer specializing in ERP Financial Systems and GenAI automation

CA, USA5y exp
OracleNYU
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VG

Mid-level Full-Stack Engineer specializing in cloud-native microservices and data integrations

5y exp
Johnson & JohnsonPurdue University
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HK

Mid-Level Backend Software Engineer specializing in Java/Spring Boot microservices on AWS

Frisco, TX4y exp
UberUniversity of Texas at Arlington
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BC

Senior Data Engineer specializing in cloud data platforms and real-time pipelines

New York, NY6y exp
DisneyIndiana Wesleyan University
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SG

Mid-Level Software Engineer specializing in AI platforms and backend systems

New York, NY6y exp
IndeedNYU
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SG

Mid-level AI Engineer specializing in LLM orchestration and production AI systems

Monroe, NJ5y exp
Shri Sai Tech LLCUniversity of Kansas
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CT

Mid-level Game Designer specializing in live service sports games

Austin, TX7y exp
Electronic ArtsChamplain College
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GC

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

USA, USA4y exp
UberTexas A&M University–Kingsville
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JK

Mid-level Data Engineer specializing in cloud data platforms and streaming pipelines

San Antonio, TX4y exp
USAAClark University
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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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SV

Senior QA Engineer specializing in test automation, API and performance testing

FL, USA10y exp
PwC
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KG

Khaliun Gerel

Screened ReferencesStrong rec.

Senior Full-Stack Engineer specializing in cloud, web, and mobile platforms

New York, NY7y exp
GertechColumbia University

Full-stack product engineer who has owned end-to-end delivery of multi-client platforms: Finy (agriculture platform with 3 role-based web dashboards plus 2 field mobile apps) and Ugoku (Japanese studio platform with React/TypeScript dashboards, Node/Mongo backend, and mobile AR video playback). Strong in scalable architecture and performance—offline-first mobile for low connectivity, and AWS-based asynchronous video/AR processing with S3/CloudFront—plus building internal ops tools adopted quickly due to measurable workflow improvements.

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AM

Abhishikth Meesala

Screened ReferencesStrong rec.

Mid-level AI/ML Engineer specializing in NLP, Generative AI, and fraud detection

Dallas, TX4y exp
PwCCampbellsville University

At PwC, built and productionized an agentic RAG enterprise search assistant over 6M internal documents (8M embeddings), deployed across AWS and GCP. Drove major retrieval gains (72%→92% precision via BM25+dense hybrid with RRF and cross-encoder re-ranking), reduced hallucinations 30%, achieved <2s latency at 50–60K queries/month, and cut support tickets 30%—boosting adoption to 2,500 users by adding source-cited answers.

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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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VM

Vamsi M

Screened

Senior QA Automation Engineer specializing in Playwright UI and API test automation

Phoenix, AZ7y exp
American ExpressUniversity of North Texas

QA automation engineer with American Express experience owning an end-to-end UI regression suite for critical payment/transaction workflows. Rebuilt the suite with Playwright (BDD/TestNG/POM) and integrated it into CI to catch release-blocking issues like UI/backend payment mismatches and session timeout defects, and applies risk-based test strategy including MFA payment flows.

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HK

Mid-Level Full-Stack Software Engineer specializing in cloud-native data platforms

Austin, TX5y exp
Northeastern UniversityPenn State University

LLM/agentic systems practitioner who specializes in moving customer prototypes into production within microservices environments, emphasizing reliability, latency, security, and measurable success metrics. Experienced in real-time troubleshooting using logs/traces and in enabling adoption through hands-on developer workshops (including live coding in Java Spring Boot) and pre-sales POCs that address technical objections and integration risk.

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SC

Mid-level Data Engineer specializing in cloud data platforms and real-time streaming

5y exp
Vertisage TechnologiesCarnegie Mellon University

Worked on onboarding a Middle East logistics client processing thousands of invoices/month, building a production-ready pipeline that routes known vendor PDFs to deterministic regex parsers via Tax ID matching and falls back to LlamaParse for unknown layouts. Added financial consistency validation plus human-in-the-loop review and logging/metrics to continuously reduce LLM usage and improve template coverage.

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