Vetted Spring Boot Professionals

Sai Haritha Sardena

Screened ReferencesStrong rec.

Mid-level Full-Stack Software Engineer specializing in web, cloud, and AI/ML

Remote, USA7y exp

“Software engineer with experience at Wipro and Tylmen Tech owning customer-facing onboarding and real-time features end-to-end (React + Spring Boot) and building TypeScript/React apps backed by Node.js microservices (MongoDB, RabbitMQ). Strong in production reliability and fast iteration: feature-flagged rollouts, idempotent APIs/consumers, DLQs, and SLO-driven incident tooling, including an internal QA & release dashboard adopted by engineering and support teams.”

Mark Thomas

Screened ReferencesStrong rec.

Director-level software architect specializing in cloud, distributed systems, and healthcare IT

McCalla, AL20y exp

“Startup veteran with experience at seven companies since 2004 and direct exposure to Birmingham's Innovation Depot accelerator through three different startups. Has worked closely with investment teams on MVPs and pitch decks and brings a pragmatic lens to evaluating ventures through need, margins, burn rate, cash position, and sales growth strategy.”

Vigneshwari Shankiri

Screened ReferencesStrong rec.

Senior Java Full-Stack Developer specializing in microservices and cloud platforms

5y exp

“Frontend engineer who has led enterprise-scale UI delivery end-to-end on a microservices platform, designing modular Angular SPAs (v12-17) tightly aligned to Spring Boot REST APIs. Emphasizes quality and release velocity through layered testing (Karma/Jasmine), CI/CD automation (Jenkins/Azure DevOps), performance tuning with RxJS/lazy loading, and incremental rollouts with close product/design/QA collaboration.”

Fatema Tuzzohra

Screened

Senior Full-Stack Java Developer specializing in banking and healthcare platforms

Hicksville, NY12y exp

“Enterprise-focused full-stack/backend engineer with hands-on experience shipping a production LLM-powered document analysis platform for internal operations teams. They combine cloud-native microservices expertise across AWS/Azure with practical agent-system design, including async orchestration, model routing, observability, and safeguards for hallucinations, failures, and human-review fallbacks.”

“Backend-focused engineer with healthcare and finance experience (Cardinal Health, JPMorgan) who has owned end-to-end data flows powering dashboards, emphasizing strong validation/data quality and measurable frontend performance gains. Has shipped Spring Boot REST APIs with versioning and Swagger docs, and has stood up an MVP task management system with GitHub Actions CI/CD, Docker, and AWS EC2 deployment.”

Nithin Reddy

Screened

Mid-Level Software Development Engineer specializing in distributed systems and event-driven architectures

Santa Clara, California4y exp

“Built and maintained an internal JavaScript/React real-time event monitoring UI used by multiple Goldman Sachs teams (e.g., Private Wealth Management and Bulk Trading Systems). Focused on scaling performance under hundreds of events/sec—using profiling, memoization, batching, and debouncing—and paired it with strong internal documentation and disciplined incident diagnosis via synthetic load testing and logs/metrics.”

“Full-stack product engineer who owned a live-events digital ticketing platform end-to-end, including blockchain-based ticket validation and high-traffic booking flows. Stands out for combining Angular/React frontend work with Java/Spring Boot backend architecture, plus strong production reliability practices around concurrency control, queues, observability, and UX optimization.”

“Backend engineer who replaced an Excel-heavy forecasting workflow with a secure, auditable FastAPI system (React UI + relational model + async workers), emphasizing deterministic processing, idempotency, and versioned ledger-style ingestion. Led a monolith-to-FastAPI migration at Bounteous using a strangler approach, feature-flagged incremental rollout, and data reconciliation/shadow-compare to protect integrity while scaling onboarding workflows.”

Vaishnavi Kashyap

Screened ReferencesStrong rec.

Junior Full-Stack Software Engineer specializing in web platforms and sustainability analytics

1y exp

“Full-stack/backend engineer who owned a production digital assembly planning platform at Saint Gobain end-to-end (React/Node/Postgres), maintaining 99.9% uptime across 5 factory sites and driving a reported 90% improvement in factory-floor coordination. Also built and operated BigQuery + Vertex AI (ARIMA) forecasting/data pipelines processing 1M+ datapoints daily, with strong emphasis on idempotency and data-quality validation to prevent incorrect outputs.”

“Built and deployed an AI Copilot for Healthful Telehealth that helps dietitians generate personalized meal plans using patient data and real-time clinical context. Stands out for owning the full lifecycle—from workflow discovery and ETL/RAG architecture to production incident response and post-launch stabilization—while delivering roughly 30% gains in retrieval accuracy and latency.”

“AI/ML Engineer (TCS) who built and deployed a production LLM-powered audit transaction validation service to reduce manual review of unstructured transaction records and comments. Implemented a LangChain/Python pipeline for extraction/normalization and discrepancy detection, with strong production reliability practices (decision logging, dashboards, labeled eval sets) and a human-in-the-loop auditor feedback loop to improve precision/recall under strict data-sensitivity and near-real-time constraints.”

suparshwa patil

Screened ReferencesStrong rec.

Mid-level Software Engineer specializing in AI platforms and full-stack systems

Santa Clara, CA4y exp

“Built and shipped a production AI-powered Q&A/RAG onboarding assistant at One Community Global that unified knowledge across Notion, Google Docs, and Slack, cutting volunteer onboarding time by 45%. Demonstrates strong end-to-end ownership: LangChain agent orchestration integrated into a FastAPI backend, rigorous evaluation (200-query dataset, ~85% accuracy), and production feedback/monitoring with source-attributed answers to build user trust.”

“Built and launched an internal AI troubleshooting assistant focused on safe, retrieval-first root cause analysis for enterprise systems, with strong attention to monitoring, fallback behavior, and post-launch iteration. Also owns full-stack product work across React and Java/Spring Boot, including high-volume financial operations workflows, and reports measurable LLM improvements such as ~30-40% latency reduction.”