Vetted Spring Boot Professionals

Mahesh Kota

Screened

Mid-level Full-Stack Java Developer specializing in cloud-native FinTech and Healthcare platforms

New York, NY5y exp

“Backend engineer with production experience building and scaling a Java/Spring Boot payment processing API on AWS (PostgreSQL/Redis) handling a few thousand RPS, including deep performance debugging (connection exhaustion) and observability (CloudWatch, Actuator, Zipkin). Also shipped application-layer AI features (OpenAI email summarizer with feedback loop, ~40% faster agent response times) and designed reliable multi-step workflow orchestration with retries and manual escalation, plus strong SQL tuning and Python engineering practices.”

Ganesh Pittala

Screened

Senior Software Engineer specializing in distributed systems and cloud-native platforms

New York, USA5y exp

“Backend-leaning full-stack engineer with experience at Walmart, Qualtrics, and American Express, shipping secure partner-facing API platforms and internal monitoring dashboards. Strong in AWS production operations (ECS/Fargate, RDS/Postgres, CloudWatch) plus rigorous testing/security practices, with measurable delivery and performance improvements (35% faster releases; ~30–40% latency reductions).”

Pranita Agrawal

Screened

Mid-level Software Engineer specializing in Java microservices and AWS

California, USA5y exp

“TypeScript backend/full-stack engineer who owned an internal business workflow platform end-to-end in production, including API/data design, relational DB integration, and enterprise integrations. Has hands-on experience operating workflow processing services with Kafka-style event-driven patterns, idempotency, exponential backoff retries, dead-letter queues, and strong observability, plus API design with OpenAPI/Swagger and token-based auth.”

“Built and shipped production LLM agents including an AI patient appointment assistant for Kyron Medical that automated specialist matching and end-to-end booking with email/SMS confirmations and a voice mode. Strong focus on production reliability (double-booking prevention with DB constraints and pre-write checks), deterministic multi-step orchestration with LangGraph, and rigorous monitoring/evaluation using LangSmith trace replay for prompt regression testing.”

Medi Val

Screened

Executive technology leader specializing in AI, digital strategy, and business transformation

Toronto, Canada25y exp

“Candidate reports being highly familiar with the venture capital and accelerator landscape, citing past experience working with VC-related environments at WINR Games and BioSymetrics. The interview ended early when the candidate withdrew their application, so detail is limited.”

Shashwat Negi

Screened

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

San Jose, CA3y exp

“Data Scientist (2–3 years) at ZS Associates who has built and productionized agentic LLM systems, including a LangGraph-based multi-LLM prompt-optimization pipeline for entity extraction deployed as a Spring Boot microservice via Jenkins. Also built an Insightmate.ai chatbot and improved its RAG accuracy by diagnosing vector retrieval issues and implementing HyDE query expansion, while partnering with sales and pharma stakeholders to drive adoption (e.g., Zimmer Biomet platform migration into a multi-year partnership).”

“Full-stack JavaScript engineer (React/Node/Vue) who has operated like a maintainer by owning an internal component library with Storybook-style examples, documentation, and non-breaking versioning. Demonstrated strong performance engineering on a source code review service—profiling bottlenecks, fixing N+1 queries, adding caching, and trimming payloads to cut latency (e.g., ~100ms to <50ms) while rolling out incremental, test-backed improvements.”

“Built from scratch a social media analytics MVP featuring an LLM-powered semantic search agent that became a core part of the product experience within a 6-week deadline. Stands out for focusing on production readiness early—retrieval-first design, explicit tool constraints, structured outputs, idempotent services, and practical eval/monitoring loops rather than demo-only AI.”

“Full-stack engineer with hands-on experience building real-time operational products across banking, insurance, and startup e-commerce environments. They’ve owned features end-to-end—from React/TypeScript dashboards and Redux performance tuning to Spring Boot, Kafka, AWS Lambda, and production monitoring—and have also shipped 0→1 capabilities where business impact was immediate, such as reducing overselling through inventory visibility.”

Meet Vyas

Screened

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

Tempe, AZ3y exp

“Software engineer with 3 years at Gap Inc. who led a major modernization from monolith/legacy frontend to a React and Spring Boot microservices architecture, delivering 25% cost savings, 30% faster releases, and 50% performance gains. Also built a 0→1 startup product, MealShare AI, using managed cloud services to rapidly launch a real-time food redistribution platform.”

“Built a production-grade LLM document processing and workflow orchestration platform at CBRE for internal operations teams, handling highly variable long-form documents with a reusable architecture involving 50+ coordinated LLM calls per request. Stands out for treating agentic systems like distributed backend infrastructure, with strong emphasis on evaluation, observability, reliability, and vendor-agnostic orchestration across Bedrock, Vertex AI, and OpenAI.”

Amit Verma

Screened

Mid-level Java Full-Stack Engineer specializing in healthcare and enterprise microservices

Birmingham, AL6y exp

“Developer who actively integrates AI tools like Copilot, ChatGPT, and Cursor into day-to-day coding, testing, debugging, and framework learning to improve delivery speed. They also organize multi-agent workflows across code generation, review, testing, and documentation while retaining final ownership of quality and architecture decisions.”

“Engineer at Morgan Stanley working on AI-enabled trade surveillance and compliance routing systems. They’ve built and monitored chained agent workflows for retrieval, risk classification, and alert routing, with strong emphasis on auditability, hallucination prevention, and regulated-environment reliability.”

“Graduate student who has built both full-stack web products and an offline Android AI assistant for visually impaired users. Particularly interesting for roles spanning product engineering and applied AI, with hands-on experience in on-device ML, privacy-sensitive deployment, and making complex AI interactions usable for non-technical users.”

Sadiya Bhawania

Screened

Senior Software Engineer specializing in AI platforms and full-stack systems

California, USA5y exp

“Full-stack TypeScript engineer with early-stage startup experience (HomePulse; sole US engineer) who ships and owns production features end-to-end—routing/state design, API contracts, caching/pagination, and post-launch monitoring/optimization. Has delivered performance-sensitive React UIs (virtualized large datasets, React Query caching, Suspense loading patterns) and built durable job-queue workflows with idempotency/retries, plus SQL Server relational modeling for internal ticketing and knowledge-retrieval workflows.”

Indra Shakya

Screened

Senior Full-Stack Engineer specializing in FinTech

Charlotte, NC8y exp

“Frontend-leaning full-stack engineer with deep experience building real-time financial trading platforms at Bank of America. They led modernization of a global markets product by consolidating three legacy apps into a single React/Next.js platform, built WebSocket-driven market data experiences, and helped drive shared component libraries and engineering standards used across multiple teams.”

Ahmed Khalafalla

Screened

Entry-level Software Engineer specializing in full-stack and backend development

Boston, MA1y exp

“Frontend/full-stack web developer with hands-on experience building browser-based applications including a social-style platform and a banking web app. Stands out for practical performance optimization work—separating frontend/backend architecture, designing APIs, reducing unnecessary rendering, and improving UI clarity through iterative user testing.”

Kuwarpreet Singh

Screened

Junior ML and Full-Stack Engineer specializing in AI/ML applications

Buffalo, NY3y exp

“Master's-trained candidate with an AI/ML specialization who combines hands-on machine learning project work with practical AI-assisted software development. They actively use Claude, ChatGPT, and Claude Code for debugging, API integration, multi-file refactoring, and end-to-end feature scaffolding, while emphasizing validation against official docs before shipping.”

Arunkumar Chockaiyan

Screened

Principal Software Architect specializing in enterprise platforms across FinTech, healthcare, and biotech

Burlingame, CA28y exp

“Senior full-stack product engineer with a track record of turning complex enterprise requirements into scalable platforms, including inventing a configurable multi-variable bidding system that expanded a B2B auction product from inventory liquidation into strategic sourcing for Fortune 100 clients. Also brings recent hands-on AI agent work, plus experience translating scientific software into usable web products and more efficient backend services in the gene-editing domain.”

“Backend/full-stack engineer who has owned production retail and order/inventory systems end-to-end, using Spring Boot microservices with Kafka event-driven workflows. Strong in production correctness patterns (idempotency, retries/DLQs, schema versioning) plus observability (Prometheus/Grafana) and developer-facing API design (Swagger, OAuth2/JWT, versioning/deprecation). Also built TypeScript/React SPAs and cited ~40% UI performance improvement.”