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Vetted Azure SQL Database Professionals
Pre-screened and vetted.
Senior Data Engineer specializing in Azure/AWS lakehouse and real-time analytics
Mid-level Data Engineer specializing in Microsoft Fabric and Azure Lakehouse platforms
Mid-Level Full-Stack .NET Developer specializing in cloud-native healthcare applications
Mid-level AI/ML Engineer specializing in LLMs, RAG, and cloud AI infrastructure
Mid-level Full-Stack Java Developer specializing in Spring Boot microservices and React
Senior Full-Stack Software Engineer specializing in .NET, Angular, and Azure cloud
Intern Full-Stack Software Engineer specializing in FinTech and compliance-focused systems
Senior Full-Stack Developer specializing in .NET, Azure, and ERP integrations
Mid-level AI/ML Engineer specializing in Generative AI for logistics and industrial systems
Senior Full-Stack Java Developer specializing in cloud microservices and web apps
Mid-Level Cloud & Systems Engineer specializing in Azure, identity/security, and automation
Mid-Level Full-Stack Java Developer specializing in FinTech and cloud microservices
Mid-Level .NET Software Engineer specializing in cloud-native enterprise applications
Senior Full-Stack Developer specializing in Azure cloud-native microservices
Mid-level AI/ML Engineer specializing in cloud AI, MLOps, and NLP
Mid-level Data Analyst specializing in marketing analytics and machine learning
Executive Technology Leader specializing in Quantum Computing, AI, and Cloud Platforms
Staff/Lead Full-Stack Software Engineer specializing in .NET, Angular, and cloud architecture
Mounika Chintala
Senior Java Full-Stack Developer specializing in cloud-native microservices
“Backend Java developer who built an end-to-end upcoming payments feature: Spring Boot/Hibernate microservices with MySQL query/index optimization and Kafka event publishing, plus a web UI timeline component enabling users to view, skip, and edit scheduled payments with clear status indicators.”
Gautam Agrawal
Mid-Level Software Engineer specializing in backend systems, cloud, and applied LLM/NLP
“Applied LLMs to classify long nonprofit mission statements into 8 segments without labeled data, using an ensemble of clustering/embedding methods plus zero-shot RoBERTa/BART and a Tree-of-Thought prompting pipeline with LLM-as-judge evaluation (Gemma). Also built LangChain/LlamaIndex agentic RAG workflows including a text-to-SQL data analysis assistant grounded on DB schema with retries and performance optimizations on an HPC cluster.”