Vetted Spring Boot Professionals

Pre-screened and vetted.

AM

Junior AI/ML Engineer specializing in GenAI, RAG, and multi-agent systems

Frisco, TX3y exp
TelecomgatewayUniversity of Texas at Arlington
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GK

Junior Software Engineer specializing in backend and full-stack systems

Buffalo, NY4y exp
Valmar Merchant ServicesUniversity at Buffalo
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JP

Senior Software Engineer specializing in FinTech platforms

United States10y exp
NeptieFlorida International University
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QQ

Entry-Level Full-Stack Software Engineer specializing in AI-driven web applications

Plano, TX
Yangzhou University
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AP

Mid-level Full-Stack Developer specializing in Java, Spring Boot microservices, and Angular

Junction City, KS5y exp
Central National Bank
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AK

Senior Full-Stack Developer specializing in automation, IoT, and integrations

Scarborough, ON, Canada6y exp
JULE
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RM

Senior Java Developer specializing in cloud-native microservices and event-driven systems

Morris, MN8y exp
Superior Industries, Inc.
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SG

Senior Software Engineer specializing in cloud-native microservices

Mesquite, Texas10y exp
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AP

Mid-Level Software Engineer specializing in Java microservices and event-driven systems

Overland Park, KS4y exp
AntraHarrisburg University of Science and Technology

Backend-focused engineer with experience spanning research and healthcare: owned a Python/SQL data pipeline that transformed vulnerability-fix code data from SQLite into model-ready JSON for LLM analysis. Also deployed Dockerized Spring Boot microservices to Kubernetes with Jenkins CI/CD and built Kafka-based real-time event streaming (appointment/report events) with idempotent consumers to avoid duplicate processing.

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TS

Tirth Shah

Screened

Mid-level AI/ML Engineer specializing in anomaly detection, data tooling, and cloud-native systems

Chico, CA4y exp
Chico State EnterprisesCalifornia State University, Chico

Backend/platform engineer who built an LLM-driven QA automation system (“mockmouse”) using a Flask orchestration microservice, Socket.IO real-time updates, Redis caching, and strict Pydantic schemas to turn prompts into reliable action graphs and automated browser tests. Has hands-on Kubernetes delivery experience (Docker/Helm/Jenkins) and has supported large migration programs, validating ETL cutovers with 1M+ synthetic records and rigorous output comparisons; also built event-driven monitoring/anomaly detection streaming into Grafana.

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SJ

Mid-Level Full-Stack Software Engineer specializing in web platforms, cloud, and test automation

San Jose, CA4y exp
San José State UniversitySan José State University

Full-stack engineer with hands-on ownership of production systems, including a Kafka-based notification/alerting platform (Node.js + React) deployed on AWS with Docker/GitHub Actions, achieving ~95% email delivery reliability. Demonstrates strong operational maturity (observability, CI/CD, zero-downtime migrations) and experience shipping in ambiguous environments (SJSU project) with evolving requirements.

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Yash Mahajan - Junior Software Engineer specializing in AI, full-stack development, and applied ML in Fullerton, CA

Yash Mahajan

Screened

Junior Software Engineer specializing in AI, full-stack development, and applied ML

Fullerton, CA2y exp
California State University, FullertonCalifornia State University, Fullerton

AI/full-stack product builder who has shipped production agentic systems in both customer support analytics and medical claims automation. They combine React/Next.js frontends with Python-based async backends and LLM orchestration, delivering measurable outcomes like 60% cost savings, 40% less manual review, and reducing claims processing from 30 minutes to 20 seconds.

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SS

Mid-level Full-Stack & Cloud Engineer specializing in backend, AWS infrastructure, and DevOps

Bradenton, FL4y exp
PM AcceleratorIndiana Wesleyan University

IBM Power/AIX engineer who has owned a large production estate (20+ Power9/Power10 frames and 400+ LPARs) with vHMC and dual-VIOS HA. Has hands-on incident recovery experience (NPIV/RMC issues, LPM restores) and PowerHA failovers, plus modern DevOps exposure using Terraform on AWS and CI/CD with GitHub Actions/Jenkins (including deploying AI/RAG and vision workloads).

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AT

Andrew Tran

Screened

Junior Full-Stack Web Developer specializing in e-commerce and React

BC, Canada2y exp
Ingram PharmacyUniversity of Victoria

Frontend-focused developer with startup/co-op experience who ships end-to-end UI features—from Figma/Canva designs to JavaScript/React implementation. Notably refactored a Bootstrap codebase to fix tablet responsiveness across every page in ~1–2 weeks, improving maintainability via semantic HTML and cleaner CSS organization. Built a React + TypeScript movie-tracking app using Firebase auth and Context-based user state, incorporating user feedback and pragmatic QA practices.

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SS

Mid-level Data Analyst specializing in dashboards, automation, and IT support analytics

Nashville, TN4y exp
Tech Masters Data SolutionsAuburn University at Montgomery

Built and productionized an LLM-powered service desk ticket triage and reporting agent that classifies, prioritizes (including sentiment/urgency), and summarizes tickets into structured SQL outputs feeding Power BI dashboards. Emphasizes production reliability (99% uptime) with retries, schema validation, confidence thresholds, human review queues, and rule-based fallbacks, delivering 85–90% reduction in manual effort and 25–30% faster resolution times.

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HK

Mid-level Data Engineer specializing in cloud ETL and big data pipelines

Naperville, IL4y exp
eAlliance CorporationLewis University

Data engineer focused on building reliable, production-grade pipelines and data services end-to-end, including a 50+ GB/day pipeline ingesting from APIs/files into Snowflake with PySpark/SQL transformations. Emphasizes strong data quality controls, monitoring/retries, and performance optimization, and has also shipped a Python data API with caching and backward-compatible versioning.

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srikanth tulluru - Mid-level Product Designer & Design Technologist specializing in design systems and GenAI UX in Remote, USA

Mid-level Product Designer & Design Technologist specializing in design systems and GenAI UX

Remote, USA3y exp
INFOTEKNOVA INC.Belhaven University

Enterprise/industrial UX designer focused on making complex, real-time automated systems feel trustworthy and predictable. Has hands-on experience observing operators in logistics/automation environments, building shared interaction models to unify fragmented products, and collaborating tightly with engineers using component-system thinking (HTML/CSS/TypeScript) to ship resilient UIs that handle partial failures.

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AV

Intern Software Engineer specializing in backend, AI, and full-stack web systems

San Ramon, CA0y exp
Antela.aiCalifornia State University, East Bay

Software engineer building AI-powered automation features in commercial real estate, including brochure generation and property listing workflows. They combine FastAPI/Redis/Celery backend architecture with multi-agent LLM design, structured prompting, testing, and production monitoring, and are now actively learning RAG and vector databases to make outputs more personalized.

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VD

Vaibhav Dabhi

Screened

Mid-level Full-Stack Engineer specializing in AI-powered web platforms

Normal, IL4y exp
Illinois State UniversityIllinois State University

Solo builder of ZenDSA, a live AI-powered DSA learning product with 37 real users, built end to end using Java/Spring Boot, React, and TypeScript. Particularly interesting for teams building AI products: they designed a production LLM fallback architecture, enforced structured JSON outputs, monitored parse-failure regressions, and fixed an SSRF vulnerability after launch.

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BK

Intern Full-Stack/ML Engineer specializing in cloud-native web apps and LLM systems

Pasadena, CA2y exp
BloophEastern Illinois University

Machine learning lab assistant at Eastern Illinois University who productionized a voice-enabled conversational AI system: redesigned it with RAG, LoRA fine-tuning (including text-to-SQL), and safety guardrails, then deployed a scalable API supporting ~1,000 daily queries. Also partnered with customer-facing teams during a BlueFi internship by building demos/APIs and accelerating releases via Terraform + AWS CI/CD automation.

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SK

Sana Khan

Screened

Mid-Level Software Developer specializing in cloud-native microservices, iOS, and ML deployment

OK, USA3y exp
Oklahoma Christian UniversityOklahoma Christian University

Backend engineer with production ERP experience deploying microservices and improving performance/reliability using a metrics-driven approach (logs, latency, error rates). Has hands-on cloud/hybrid operations across AWS and Azure with Docker/Kubernetes, and has resolved real-world mobile sync issues by tuning timeouts/retries and reducing payload sizes. Builds configurable Python services to deliver customer-specific behavior without destabilizing the core codebase.

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AD

Amer Damaj

Screened

Junior Full-Stack Software Engineer specializing in cloud-native web apps and APIs

Toronto, Canada2y exp
UntoldcineLebanese American University

Built a voice-driven desktop assistant for users with mobility impairments, integrating Whisper and Google Gemini and adding voice-authentication via speaker embeddings for secure command execution. Has hands-on experience with AWS serverless/microservices patterns (Lambda, S3, CloudFront, CloudWatch) and CI/CD, plus built an internal MySQL-to-MongoDB migration tool used by the CTO and dev team with an emphasis on safe, low-impact data transformation.

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Venkata Bayarapuneni - Junior Full-Stack Developer specializing in JavaScript, Python, and cloud-deployed web apps in Remote, USA

Junior Full-Stack Developer specializing in JavaScript, Python, and cloud-deployed web apps

Remote, USA1y exp
BlackBuck EngineersUniversity of Central Missouri

Built and deployed a production LLM-powered travel assistant (Globe Trote) that automates end-to-end trip planning using a multi-step agent pipeline with RAG, external API calls, and enforced structured JSON outputs. Focused on reliability (validation, retries, fallback prompts, logging) and reported a ~30–40% reduction in irrelevant/generic responses after adding retrieval grounding.

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