Vetted Spring Boot Professionals

Vidhi Chhatbar

Screened

Mid-level Full-Stack Engineer specializing in cloud microservices and FinTech

Los Angeles, CA5y exp

“Software engineer with experience across enterprise (AIG, MSCI) and an early-stage startup (Job Map), owning production systems end-to-end. Built secure insurance microservices on Spring Boot with JWT/RBAC and AWS-based CI/CD/observability, plus Kafka streaming pipelines for financial data. Also shipped a GenAI personalization MVP using FastAPI and LLM APIs in a high-ambiguity startup environment.”

“Built and deployed an AI-powered insurance claims fraud platform end-to-end using Java/Spring Boot, Kafka, OpenAI, pgvector, and AWS EKS. Stands out for combining LLM/RAG architecture with production-grade scalability and observability, delivering measurable impact including 62% less manual review, 40% better fraud precision, 37% higher throughput, and 99.95% uptime.”

“Senior software engineer with hands-on experience leading multi-agent AI workflows in financial trading infrastructure. Most notably, they applied a specialized agent setup on a high-frequency trading backend to cut delivery time from three weeks to ten days while improving validation against risk, performance, and compliance requirements.”

Neeshma Narahari

Screened

Mid-level Software Developer specializing in backend microservices and cloud platforms

Irving, TX6y exp

“Full-stack product engineer with strong React and TypeScript depth who has owned dashboard features end-to-end, from UI architecture and rendering optimization through Spring Boot APIs and database query tuning. Particularly compelling for startup or high-growth teams: they’ve shipped 0→1 internal operations platforms, prioritized MVP workflows effectively, and iterated post-launch using user feedback, logs, and usage metrics.”

“Built end-to-end financial workflow platforms at Citi spanning React frontends, Spring Boot microservices, Kafka, Redis, and Oracle. Particularly compelling for teams needing someone who can modernize legacy systems into real-time architectures—the candidate cites a 48x throughput improvement from a batch-to-Kafka modernization effort.”

“Backend engineer with hands-on experience building event-driven Java/Spring Boot and Kafka systems, plus AI-assisted document-classification workflows in enterprise environments. Stands out for a thoughtful, risk-aware approach to AI: uses it to accelerate delivery, but emphasizes validation layers, confidence thresholds, observability, and human review before AI can affect downstream business actions.”

“Frontend/full-stack engineer with Chegg experience shipping signed-in and top-of-funnel Next.js experiences, including leading an account-sharing/device-management MVP integrated with a Java Spring Boot service. Stands out for strong rollout ownership, analytics-based validation, and pragmatic security/performance decisions in production.”

“Frontend engineer with experience spanning Amazon Seller Central, Shoptaki, and TCS, focused on turning complex, dynamic workflows into scalable browser-based systems. Particularly strong in schema-driven and metadata-driven UI architecture, including AI-powered analytics interfaces and compliance platforms where adaptability, consistency, and trust are critical.”

Henry nguyen

Screened

Senior Full-Stack Engineer specializing in FinTech and mobile platforms

Dallas, TX6y exp

“Built WalletBuddy, a personal credit card tracking app, end to end using React Native, TypeScript, Convex, and agent-based web research workflows to maintain a 130+ card catalog. Also operated as a solo lead in a constrained Citi environment, rapidly shipping Python/Postgres ETL pipelines for stakeholder reporting while making pragmatic decisions about where AI automation should and should not be used.”

“Software engineer with Intuit experience shipping an end-to-end real-time financial insights product on AWS, using event-driven architecture with Kafka and Spark Streaming to process millions of records with low latency. Also delivers customer-facing React + TypeScript dashboards and has hands-on production operations experience, including resolving a database scaling incident via read replicas, query tuning, and connection pooling.”

“Backend engineer who built a Logistics-as-a-Service platform in Go, proactively refactoring a monolithic REST service into gRPC microservices to improve performance and maintainability. Led a 3-person team with disciplined code reviews, Dockerized DB migrations, and a canary-style rollout (5% traffic) monitored for latency and failures; also implemented JWT/OAuth2 RBAC and production-minded edge-case handling in an ordering system.”

“Enterprise platform engineer/product owner who led end-to-end delivery of customer-facing ServiceNow Service Catalog/workflow solutions, emphasizing reliability, security, and fast iteration. Built React/TypeScript portals with Node.js and Spring Boot backends, and improved microservices reliability at scale using Kafka, monitoring, and robust retry/timeout patterns.”

“Software engineer with deep experience in real-time payments and event-driven microservices. Built a React/TypeScript + Spring Boot system using RabbitMQ, and created an internal operations dashboard that improved visibility into message-processing workflows for engineering, support, and SRE. Strong in experimentation-driven product iteration (feature flags/A-B tests) and in scaling reliability via idempotent consumers and end-to-end observability.”

“Amazon engineer who built a production AI agent platform (Python/AWS Strands on Bedrock) that lets teams create tool-using, multi-agent workflows—e.g., agents that auto-triage and resolve customer support tickets by reading internal documentation and collaborating with a research agent. Previously worked in Deloitte on IAM using Ping Identity/Ping DaVinci orchestration, and applies orchestration thinking plus structured evaluation (LLM-as-judge, surveys, automated tests) to improve agent reliability.”

“Backend engineer focused on Python/FastAPI microservices, with hands-on experience deploying to AWS (EKS/ECR) via Jenkins and GitOps-style workflows using ArgoCD. Has built and stabilized real-time Kafka payment-event streaming pipelines and improved production performance under peak load through Redis caching, SQL optimization, and robust retry/DLQ patterns. Also supported phased migrations from on-prem environments to AWS with gradual traffic shifting and monitoring.”

“Built and productionized an autonomous research agent (AutoGPT) in a Docker/Kubernetes environment with Pinecone-based long-term memory and custom Python tools for analysis, visualization, and report drafting. Implemented layered guardrails (prompt templates, automated validation, self-critique loops, and monitoring) and achieved ~25% reduction in manual report generation time while scaling the workflow to support multiple concurrent users.”

“Built and productionized an NLP-powered customer support assistant at JPMorgan Chase for digital banking, focused on reducing response time for repetitive client queries. Strong in real-world AI deployment challenges—sensitive data handling, low-latency FastAPI services, and AWS/Kubernetes operations with CI/CD—plus a metrics- and guardrails-driven approach to reliable AI workflows.”

“Full-stack engineer (backend-led) with recent experience building enterprise workflow orchestration and billing/payment platforms at Intuit using Java/Spring Boot (WebFlux), Kafka, Postgres/Redis, and React/TypeScript. Has operated at high scale (reported ~1200 RPS during month-end billing) and focuses on event-driven microservices, real-time UI updates via streaming, and disciplined API evolution with contract testing.”

“Engineering leader (Credit Karma/fintech) who built internal developer-platform frameworks at near open-source scale, including a unified key management system migrating ~450 services from on-prem HSM to a centralized KMS. Known for driving large cross-team migrations with strong safety mechanisms (canaries, shadow reads, rollback toggles) and measurable DX/ops improvements (60% fewer provisioning requests; 40% faster time-to-first-secret).”

“Built a lightweight internal JavaScript analytics tracker capturing user interactions (clicks, page views, custom events) with debounced batching, automatic session tracking, and offline event caching via a localStorage-backed append-only queue. Demonstrates practical performance optimization mindset (profiling, memoization/caching) and React performance tuning.”

“Backend/platform engineer from Fanatics sportsbook core team with deep experience in real-time ingestion systems (Kafka) and high-throughput performance optimization. Delivered an 87% latency reduction on a Java API handling hundreds of thousands of updates per second, and improved reliability of shared internal libraries via deterministic recovery logic, strong testing, and feature-flagged rollouts.”

“Backend engineer who has led major platform evolution to cloud-native microservices (Spring Boot on AWS with Terraform) and built scalable, secure FastAPI APIs. Demonstrates strong production rigor with metric-driven validation, canary/phased rollouts, and incremental migrations using shadow traffic/feature flags/parallel writes—achieving faster deployments, fewer incidents, and zero-downtime traffic spikes and migrations.”

“Software engineer in the mortgage/financial services domain (Freddie Mac) who builds end-to-end loan origination and credit risk capabilities using Spring Boot microservices, Angular dashboards, and data pipelines. Delivered measurable impact (30% reduction in underwriting turnaround time) and emphasizes production reliability/compliance with strong guardrails, observability, and evaluation loops for risk scoring systems.”