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Vetted gRPC Professionals
Pre-screened and vetted.
Abdelmonaim Serrhini
Senior Full-Stack Engineer specializing in Spring Boot, React, and Next.js
“Full-stack engineer and Scrum Master who led a major monolith-to-microservices migration, including a micro-frontend Angular architecture using Native Federation and staged integration into the legacy app. Also built a React + TypeScript “Business Risk” product featuring a metadata-driven dynamic dashboard/forms layer backed by Spring Boot + GraphQL, with strong QA practices (unit/integration/E2E via Cypress), CI/CD, and feature toggles.”
Marshal Kalaria
Senior Full-Stack Developer specializing in cloud-native microservices (Angular/React, .NET, Java)
“Full-stack engineer with experience delivering an end-to-end NIH application using Angular and scalable .NET Core microservices backed by MySQL. Has hands-on depth in complex approval/workflow implementations (RBAC + workflow engine) and performance tuning for million-record, data-driven systems, plus 5 years with Java/Spring Boot microservices and React.”
Entry-Level Full-Stack AI Engineer specializing in RAG pipelines and enterprise SaaS
Junior Full-Stack Software Developer specializing in cloud-native apps and data/AI
Mid-level Full-Stack Developer specializing in Python, React, and cloud-native microservices
Maulik Maganbhai Ghatala
Entry Backend Software Engineer specializing in Python/FastAPI and cloud-native APIs
“Backend engineer who built and evolved a low-latency document search platform (C++/gRPC on Kubernetes with a vector database), emphasizing resilience under concurrent load through strict deadlines, retries, idempotency, and observability. Also experienced building secure, frontend-friendly FastAPI services (Pydantic + JWT) and executing safe incremental refactors using feature flags and parallel validation.”
Entry-Level Full-Stack Software Engineer specializing in backend systems and cloud deployment
Mohammad Rostom
Intern Full-Stack Software Engineer specializing in AI-powered RAG systems
“Built FlowPilot, an AI-powered product that generates complete importable n8n workflows from natural-language prompts using a RAG pipeline (Qdrant + LangChain) and a multi-stage agent with a scoring/repair 'Judge' loop for intent alignment. Experienced in backend architecture across Laravel/Node microservices and production AI/RAG systems, plus performance debugging from async job offloading to database index tuning after ORM migrations.”
Junior Full-Stack Software Engineer specializing in web and backend systems
Naman Limani
“Built multiple AI projects end-to-end as a solo developer, including a privacy-focused LLM app that redacts PII before sending prompts to an external model and a LangGraph-based multi-agent triage system for log analysis. Stands out for combining LLM/agent design, deployment troubleshooting, and practical workflow automation with a strong emphasis on privacy and explainability.”