Vetted Swagger Professionals

“Backend engineer with experience modernizing a large-scale procurement platform at Jio Platforms by breaking a monolith serving 35 business units into Spring Boot microservices, improving uptime and cutting report latency ~30%. Also built high-concurrency FastAPI systems (200ms at ~500 concurrent users) with strong security (JWT/OAuth2/RBAC), event-driven Kafka integrations, and reliability patterns like exactly-once delivery for ~1M monthly triggers.”

“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.”

“Full-stack engineer who built and owned an internal analytics dashboard for sales (React/TypeScript + Node/Express + NoSQL), delivering it two weeks early with zero production issues and a reported 10% sales-efficiency lift. Experienced with microservices and async messaging patterns (retries/DLQs/idempotency), and emphasizes rapid iteration with strong CI/CD and automated testing plus user-driven adoption.”

“Backend engineer with Walmart experience owning Python data-processing/integration services alongside ASP.NET Core. Has deployed containerized services to Kubernetes via OpenShift with Jenkins CI/CD and GitOps-style config management, and has led phased migrations modernizing VB6/classic ASP apps to ASP.NET Core on OpenShift/Azure. Also implemented Kafka-based real-time pipelines with a focus on reliability, idempotency, and observability.”

“Backend engineer at Cerebrone.ai building cloud-native Flask microservices for an AI-driven automation platform on GCP (Cloud Run/App Engine), including dedicated inference services integrating OpenAI and internal ML pipelines. Demonstrated strong performance and scalability wins across Postgres/SQLAlchemy optimization, multi-tenant (healthcare/HIPAA-grade) data isolation, and high-throughput background processing with Celery/Redis/RabbitMQ, with multiple quantified latency/CPU/throughput improvements.”

“Backend engineer on Morgan Stanley’s trade risk and compliance platform, building Java/Spring Boot microservices that validate equity and fixed-income trades at multi-million-events/day scale. Shipped an LLM-assisted trade exception analysis feature using RAG over internal policy documents and trade history, with production-grade guardrails (confidence thresholds, audit logs, human-in-the-loop) and measurable performance wins (~30–35% faster reporting) through PostgreSQL tuning and Redis caching.”

“AI/ML engineer at Cigna Healthcare building a production, HIPAA-compliant LLM-powered clinical insights platform that summarizes unstructured medical notes using a fine-tuned transformer + RAG on AWS. Demonstrates strong end-to-end MLOps and cloud optimization (distillation, Spot/Lambda/Auto Scaling) with quantified outcomes (~28% accuracy lift, ~40% less manual review, ~25% lower ops cost) and strong clinician-facing explainability via SHAP and dashboards.”

“Software engineer with payments-domain experience (Visa) building real-time transaction monitoring and analytics systems. Strong end-to-end ownership across Spring Boot/Kafka microservices, PostgreSQL modeling, and AWS/Kubernetes operations, plus React+TypeScript dashboards—focused on low-latency processing, secure APIs, and zero-downtime production releases.”

“Internship at ActiveVM where they tackled large-scale Spring Boot 2→3/library migrations across hundreds of downstream products by combining OpenRewrite (AST-based recipes) with an LLM/RAG-based classifier that routed risky files to human experts. Reported ~70% reduction in manual effort and 90%+ accuracy after testing across multiple branches and cutovers; also built a CTR-driven book recommendation capstone showcased at the Google office in Cambridge.”

Gnaneswar Markat

Screened

Mid-level Software Engineer specializing in cloud-native distributed systems

Charlotte, NC4y exp

“Full-stack engineer with Bank of America experience building and owning a customer portfolio dashboard end-to-end, from requirements through launch and ongoing iteration. They combine React/Spring Boot/PostgreSQL implementation with strong performance tuning, real-time data handling, and UX improvements, and cite adoption by roughly 12,000 active internal users.”

“Built Nexthire-AI, shipping an end-to-end LLM-powered resume–job description matching product (React + Node.js) using embeddings and retrieval to generate match scores and skill-gap recommendations. Improved post-launch engagement by making feedback cleaner and more actionable, and added production guardrails (validation, timeouts, fallbacks) to handle messy resume formats and AI API instability.”

Anudeep Eloori

Screened

Mid-level Software Developer specializing in full-stack enterprise applications

USA3y exp

“Software engineer with experience building and iterating high-volume Spring Boot microservices on AWS (Docker/Kubernetes) and integrating with React front-ends. Also delivered an LLM-powered document summarization system using embeddings + retrieval (RAG) with grounding/guardrails and built evaluation loops that directly drove retrieval and chunking improvements. Has scaled Kafka-based pipelines processing millions of messy financial/infrastructure records with reliability and cost/latency tradeoff management.”

“Built internal product features at Sysco's Collab Cafe across React/TypeScript frontend and Spring Boot/PostgreSQL backend, including a full project invite flow and an early AI-style project matching capability. Stands out for owning features end-to-end, improving React dashboard performance with profiling and component refactoring, and making pragmatic 0→1 tradeoffs to ship quickly.”

“Banking-focused full-stack engineer who has owned products from requirements through deployment, including a transaction review dashboard and an AI-assisted search tool for internal support teams. Brings a strong mix of React/TypeScript, Spring Boot, database performance tuning, and practical LLM/RAG experience with human-in-the-loop safeguards for regulated workflows.”

“Frontend engineer with production experience at UWM and Ford.com, focused on complex UI architecture, dynamic form systems, and high-performance interactive experiences. Stands out for rebuilding problematic React/Redux patterns into reactive RxJS-driven architectures, with measurable wins like reducing an 8-second, 5,000-request widget to a fast, stable experience, and for also building advanced personal projects in Solid.js, mapping, and WebGL.”

“Backend engineer who built an e-commerce order processing service in Python/Flask with PostgreSQL, focusing on correctness and reliability (idempotency, Redis locks, async payment processing with circuit breakers). Also integrated an ML recommendation system as a separate FastAPI inference service with caching and async embedding updates, reporting ~25% CTR lift, and has experience with multi-tenant isolation using PostgreSQL row-level security.”

“Full-stack engineer focused on enterprise, cloud-native microservices—building Spring Boot backends and React/Angular front ends with strong security (OAuth/JWT), AWS infrastructure (RDS/S3), and containerized deployments (Docker/Kubernetes). Has delivered data-heavy order/account/transaction platforms and healthcare solutions including EHR integrations for secure patient data exchange, with emphasis on testing, performance tuning, and reliability (load testing).”

“Backend engineer who has delivered large, measurable performance wins (10x throughput, 67% latency reduction) by combining Flask microservices, Redis caching, and AWS autoscaling/observability. Has hands-on depth in SQLAlchemy/Postgres optimization and production scaling pitfalls (cache consistency, connection exhaustion), plus experience deploying real-time ML inference (XGBoost) on AWS Lambda and building secure multi-tenant Kubernetes isolation.”