Vetted Gradle Professionals

“Capgemini engineer with 4+ years building and deploying high-availability, low-latency fraud detection APIs and multi-cluster distributed systems for a Fortune 20 bank, including zero-downtime production rollouts and multi-layer (SQL/network/hardware) performance debugging. Also built a Python + OpenAI/LangChain LLM-powered grading workflow for Austin School for Women, cutting feedback time from 90 minutes to 5 minutes per submission for 200+ learners.”

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.”

“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 currently at Citigroup working on real-time transaction processing systems with Kafka. Stands out for using AI tools pragmatically in a regulated banking environment to improve debugging, testing, and developer productivity while keeping human control over architecture, security, and performance decisions.”

“ML/AI practitioner in healthcare (Syneos Health) who has deployed production clinical NLP and risk models. Built a BERT-based physician-note information extraction system on Docker + AWS SageMaker (reported ~42% retrieval improvement) and automated retraining/deployment with Airflow and drift detection, while partnering closely with clinicians to drive adoption (reported ~18% readmission reduction).”

“Software engineer with strong full-stack and platform experience (TypeScript/React/Node.js) who has built real-time analytics dashboards and microservices using RabbitMQ. Demonstrates production-minded decision-making under launch pressure (manual fallback for payment-impacting third-party API issues) and has delivered internal DevOps tooling that automates compliance checks via GitHub/Jira integrations.”

“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.”

“Deloitte engineer who built and shipped AI-powered, Kafka-driven workflow automation for transportation/document processing, including LLM-based semantic search. Strong in production reliability (idempotency, offset management, retries), observability (Datadog/CloudWatch), and database performance tuning (PostgreSQL/Flyway), with measurable latency 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.”

“Azure cloud platform engineer with strong enterprise Linux operations background who designs multi-region HA/DR on Azure (and AWS) using Azure Site Recovery, Traffic Manager, AKS autoscaling, and geo-replicated Azure SQL. Built secure Azure DevOps CI/CD pipelines for .NET/Python microservices to AKS/VMs and provisions full environments via Terraform modules with remote state, drift checks, and staged rollouts; has not directly owned IBM Power/AIX at scale.”

“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.”

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.”

“Backend/data engineer with hands-on production experience across Python REST APIs and PostgreSQL, plus AWS containerized deployments using CloudFormation, Jenkins CI/CD, and CloudWatch monitoring/autoscaling. Has built data validation/ETL-style workflows with schema/version checks and targeted reprocessing, modernized legacy batch processing into Java services with phased parallel migrations, and delivered measurable SQL performance gains (~50% query runtime reduction).”

“Software engineer with a CS/Computer Engineering background who has worked on ML/NLP (Hugging Face, clinical NLP, text generation and structured extraction) and has a school robotics project integrating a trained ML model with microprocessor-controlled hardware to drive motor movement and writing. Currently focused on building and deploying applications and ML models to AWS/Azure using Docker, Kubernetes, and CI/CD; targeting ~$150K compensation.”