Vetted JUnit Professionals

“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.”

“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.”

“Full-stack engineer who built and supported production features in a productivity/task-tracking app using Next.js App Router + TypeScript (server components for initial render, client components for interactivity, API route handlers for mutations). Also designed and optimized Postgres data models/queries and implemented resilient, event-driven payment processing with idempotency, retries, audit logs, and strong testing/observability practices.”

“Data engineer with hands-on experience migrating a legacy/mainframe-fed loader onto GCP, orchestrating daily SFTP-to-GCS ingestion, Spark/Scala transformations, and loading into Cassandra/Solr/OpenSearch with API- and BigQuery-based validation. Also built a Java Spring Boot service that extracts from Hive and produces Excel outputs, emphasizing testing, logging/alerts, and CI setup.”

Arjun Masadi

Screened

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

Remote, USA3y exp

“Full-stack engineer (3+ years) who owned an AI-powered customer financial health dashboard end-to-end at Regions Bank, combining React/Java Spring Boot with LangChain + Pinecone for personalized insights. Strong production operations experience on AWS EKS with CI/CD and observability (OpenTelemetry/Prometheus/Grafana), delivering measurable outcomes including 22% support reduction and 99.9% uptime, plus robust third-party financial/clinical integrations.”

Kalyan Reddy

Screened

Mid-level QA Engineer specializing in manual, mobile, and API testing

Alabama, US4y exp

“QA automation engineer who owned end-to-end test automation for a web-based enterprise application, building and scaling suites in Selenium/Java/TestNG and Cypress/JavaScript. Strong in CI/CD integration with PR gating and actionable reporting, and has prevented high-severity auth/session regressions by catching role-based login/token issues early via automated CI runs.”

Priyanshi Sharma

Screened

Mid-level Software Engineer specializing in FinTech full-stack and backend systems

Parsippany, NJ4y exp

“Built and productionized a GenAI prompt-engineering solution to retrieve prevailing wages based on job/location selections, emphasizing accuracy through stricter prompt templates and validation. Hands-on in real-time production debugging using Splunk (callback tracing, verbose logging, header inspection) and experienced running developer-facing demos/workshops that helped drive marketplace API adoption.”

“Startup-oriented product/technology leader targeting CTO roles, with experience evaluating and scoping high-impact product expansions. At Crelate, helped assess and shape a contract timekeeping/invoicing initiative that expanded TAM by hundreds of millions and increased ACV 2-3x, contributing to successful market traction and the company’s path to Series C.”

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.”

Sangita Satapathy

Screened

Senior Full-Stack Engineer specializing in FinTech and AI applications

Las Vegas, NV11y exp

“Engineer with a pragmatic, production-focused approach to AI development, using tools like Copilot and ChatGPT to accelerate coding while maintaining strong engineering fundamentals. Has led a RAG-based multi-stage AI solution spanning retrieval, context building, and response generation, with an emphasis on validation, prompt quality, and reliability.”

“Software developer with a one-year Philips co-op who has already applied AI-assisted coding in production, not just side projects. Stands out for using multi-agent development setups with task-specific sub-agents and a clear human-led orchestration philosophy focused on context, quality control, and security.”

“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.”

“Engineer with a process-driven approach to AI-assisted software development, focused on orchestrating where AI adds value while maintaining human review and verification. Has applied this in backend work such as an S3-based invoice pipeline and used multi-agent workflows to speed up large API refactors across many endpoints.”

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.”

“Backend-oriented software engineer who uses AI as a disciplined engineering accelerator rather than a replacement for judgment. They have hands-on experience coordinating multiple AI tools/agents across code generation, testing, debugging, and review, with strong emphasis on security, scalability, and human validation before production use.”

Namratha Medaboina

Screened

Mid-level Software Engineer specializing in backend systems for healthcare and FinTech

3y exp

“Built Python-based clinical data processing workflows at CVS Health, automating ingestion, validation, transformation, and ML prediction across multiple healthcare systems. Stands out for combining AI-assisted development with rigorous human review, validation checkpoints, and production monitoring in regulated healthcare environments, including a reported ~26% efficiency improvement.”

“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.”

Vinay K Naidu

Screened

Senior Full-Stack Engineer specializing in Healthcare IT and FinTech

5y exp

“Built and shipped a production LLM-powered incident assistant integrated with monitoring, logs, and metrics systems that reduced triage time by 30–40% and improved MTTR. Stands out for a strong reliability-first approach to agent design, including deterministic orchestration, strict schemas, fallback flows, grounding checks, and safeguards for messy operational data.”

“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.”

Priyadarshini Vykuntapu

Screened

Mid-level Software Developer specializing in full-stack systems for FinTech and industrial platforms

USA3y exp

“Enterprise full-stack engineer with experience at Honeywell and Wells Fargo, spanning real-time telemetry dashboards and digital banking systems. Stands out for owning production systems end to end, improving performance in high-scale environments, and driving architectural modernization that reduced release times and improved reliability.”