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Vetted Software Engineers in Remote
Pre-screened and vetted in Remote.
Mid-level Full-Stack Developer specializing in cloud-native microservices and FinTech risk systems
Senior Software Engineer specializing in AI agents, RAG systems, and cloud microservices
Mid-level Software Engineer specializing in FinTech platforms and real-time analytics
Mid-level Software Engineer specializing in backend systems and LLM/RAG applications
Mid-level Software Engineer specializing in FinTech ML and cloud-native microservices
Mid-level Software Engineer specializing in cloud-native microservices and data platforms
Mid-level Full-Stack Software Engineer specializing in cloud-native apps and GenAI
Mid-level Full-Stack Engineer specializing in AI, LLM/RAG platforms, and data systems
Junior Full-Stack Software Engineer specializing in React/Next.js and Node.js
Senior Full-Stack Software Engineer specializing in React, TypeScript, and Python
Mid-Level Software Engineer specializing in full-stack and AI-enabled backend systems
Mid-level Full-Stack Software Engineer specializing in cloud backend and AI infrastructure
Senior Full-Stack Engineer specializing in frontend modernization and LLM-enabled enterprise apps
Mid-level Java Full-Stack Developer specializing in microservices and cloud-native systems
Pavani Tummuru
Mid-Level Software Engineer specializing in full-stack microservices and cloud platforms
“Software engineer experienced owning internal, customer-facing dashboards and internal ops tools end-to-end, emphasizing fast iteration without sacrificing stability (CI/CD, automated tests, feature flags, monitoring). Built a TypeScript/React role-based dashboard backed by Java Spring Boot and has hands-on microservices experience with RabbitMQ, including production hardening with retries, dead-letter queues, logging, and health checks.”
Dharshini Nithila Muruganithi
Mid-Level Software Engineer specializing in Python backend and React full-stack development
“Backend engineer who built and optimized a high-traffic e-commerce platform in Python/Flask, focusing on scalability and reliability through service decomposition, Redis caching, and Celery-based background processing. Also integrated an AI intent-classification chatbot as a separately deployable inference service on AWS and has hands-on experience designing multi-tenant data isolation strategies in PostgreSQL.”
Abhishek Panda
Junior Software Engineer specializing in cloud-native microservices and ML/LLM pipelines
“Backend-leaning full-stack engineer who ships AI-enabled products end-to-end: built CodeChat, a production internal codebase Q&A tool using RAG with Pinecone and a model-agnostic wrapper across OpenAI/Anthropic/AWS Bedrock, cutting AWS costs ~50% and latency ~45%. Also built and operated RealityStream, a Flask-based real-time forecasting API with JWT/RBAC, MLflow model versioning, and Prometheus/Grafana observability, including handling a real production latency incident via rollback, preloading, and caching.”