Vetted Oracle Database Professionals

Pre-screened and vetted.

JR

Mid-level Full-Stack Engineer specializing in React and Java microservices

New York, United States5y exp
UberFullstack Academy
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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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SS

Mid-level Backend Software Engineer specializing in FinTech and cloud microservices

Bellevue, WA4y exp
UberAuburn University at Montgomery
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SA

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

Dallas, TX4y exp
eBayUniversity of North Texas
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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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MS

Senior Solution Consultant specializing in Workday HCM and integrations

5y exp
Elevance HealthUniversity at Albany
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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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SK

Sangeeth Kumar Mohan

Screened ReferencesModerate rec.

Senior Lead Software Engineer specializing in authentication platforms and distributed systems

15y exp
T-MobileLincoln University

Full-stack engineer (T-Mobile experience) focused on authentication/session-management systems, with hands-on work optimizing token-validation flows and reducing latency by eliminating redundant API calls and adding caching. Brings strong production ownership with observability (Splunk/Grafana), Postgres data modeling/index tuning, and resilient async workflow design (idempotency, retries/backoff, queues).

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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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JB

John Barker

Screened ReferencesStrong rec.

Executive Operations & Service Delivery Leader specializing in BPO, HRO, Payroll, and Finance services

Fort Lauderdale, Florida29y exp
FMS SolutionsLoyola University Chicago

Operations leader with experience standing up and scaling a bespoke, high-growth services operating model at ADP (Comprehensive Services), including SOP standardization, BPM/workflow deployment, and analytics/automation enablement. Reports major outcomes including 99.5%+ accuracy, NPS 71, and a turnaround from losses to significant profitability growth, with a metrics- and governance-driven approach to change management and executive advising.

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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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JR

Jugal Rayala

Screened

Mid-level Full-Stack Developer specializing in AI-powered cloud applications

Remote, USA5y exp
MicrosoftWebster University

Full-stack engineer who has owned customer-facing AI recommendation and analytics dashboards end-to-end (backend APIs/data processing through React UI, deployment, and monitoring). Demonstrates strong systems thinking around scaling microservices—using observability, caching, async workflows, and resilience patterns—and also built an internal ops dashboard that became the default tool for on-call incident reviews.

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AS

Abraham Song

Screened

Director-level Programmatic & Ad Operations leader specializing in performance and commerce media

Decatur, GA30y exp
Mars United CommerceEmory University

Performance marketer with hands-on ownership of large Coca-Cola programmatic/retail media spend across The Trade Desk, Amazon DSP, and Walmart DSP, focused on ROAS and sales outcomes. Experienced in validating incrementality and attribution by benchmarking retailer first-party measurement against third-party partners (Foursquare/InMarket), and has delivered measurable lifts (e.g., 2x ROAS on Core Power; 1.5x–2x sales/ROAS recovery on Fairlife after audience + creative/video refresh).

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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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MM

Meet Merchant

Screened

Mid-level Software Engineer specializing in LLM agents and full-stack systems

Redlands, California3y exp
EsriUC Irvine

At Esri, the candidate is building a production LLM-powered WebGIS AI framework that embeds an AI assistant into web maps and routes natural-language requests into ArcGIS JavaScript SDK functions via a LangGraph-orchestrated, multi-agent system. They emphasize production reliability and scale (strict tool calling/JSON, live schema validation, query guardrails) and rigorous evaluation/observability using LangSmith, offline prompt datasets, and latency/tool-call accuracy tracking.

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AD

Aarati Dulal

Screened

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

Dallas, TX6y exp
Goldman SachsAvila University

Backend/platform engineer who owned high-volume Java/Spring Boot microservices on AWS (Kafka + RDS/DynamoDB) and has hands-on experience debugging complex production latency incidents across DB, JVM/GC, and async consumers. Also shipped applied AI features for ops, including an LLM-powered log analysis assistant and an incident-response agent with strong safety guardrails (schema-validated tool use, retries/backoff, and human-in-the-loop escalation).

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Rahul Kushwaha - Mid-level Software Engineer specializing in FinTech and scalable microservices in Texas, USA

Mid-level Software Engineer specializing in FinTech and scalable microservices

Texas, USA5y exp
PayPalSanta Clara University

Backend/platform engineer focused on high-traffic financial systems, owning real-time event-driven ingestion and Kafka streaming pipelines using Python/FastAPI, Avro schemas, and AWS services. Has hands-on Kubernetes (EKS) and GitOps/CI-CD experience (ArgoCD/Jenkins) and supported large-scale migrations from legacy VMs to containerized microservices with zero/low-downtime cutovers.

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SS

Sayuj Shah

Screened

Mid-level Data Analyst & AI Practitioner specializing in ML, LLMs, and analytics platforms

Schaumburg, IL4y exp
U.S. CellularGeorgia Tech

Data Analyst at U.S. Cellular who built production LLM solutions, including a Tableau-embedded chatbot that converts natural language questions into Oracle SQL and returns actionable KPI insights for non-technical users. Also authored MAD-CTI, a multi-agent LLM system for dark web hacker forum threat intelligence (published in IEEE Access) that outperformed single-agent approaches by 14%.

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DK

David Kidwell

Screened

Senior AI/ML Data Scientist specializing in NLP, computer vision, and MLOps

New York, NY10y exp
Canoe IntelligenceBinghamton University

Applied LLMs and a graph-RAG architecture in Neo4j to automate an accounting firm's cross-checking of transactional books against tax regulations, indexing 1,000+ pages into a knowledge graph with vector search. Combines agentic LLM workflows with classical NER (Hugging Face/NLTK) and validates using expert-labeled held-out data plus precision/recall and measured accountant time savings after deployment.

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