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Vetted Amazon RDS Professionals
Pre-screened and vetted.
Mid-level Full-Stack Software Engineer specializing in cloud microservices and ML integration
Mid-Level Software Developer specializing in cloud-native microservices and FinTech
Mid-Level Software Engineer specializing in cloud-native microservices and distributed systems
Mid-level Software Engineer specializing in AI and cloud-native data platforms
Senior Full-Stack Engineer specializing in cloud-native platforms, DevOps, and Kubernetes
Mid-level Backend Software Engineer specializing in cloud microservices and distributed systems
Mid-Level Full-Stack Software Developer specializing in AWS cloud and microservices
Mid-level Full-Stack Java Developer specializing in FinTech and cloud microservices
Junior Full-Stack Developer specializing in AI and cloud-native systems
Mid-level GenAI/ML Engineer specializing in RAG, semantic search, and LLM systems
Mid-Level Software Engineer specializing in distributed systems and cloud platforms
Senior Full-Stack Software Engineer specializing in AWS, .NET, and data/telemetry platforms
Mid-level Software Engineer specializing in backend systems, APIs, and cloud microservices
Mid-level Software Developer specializing in DevOps, CI/CD, and AWS Kubernetes
Senior Full-Stack Software Engineer specializing in AI-native enterprise products
Mid-level DevOps Engineer specializing in Azure cloud infrastructure and CI/CD
Mid-level Full-Stack Software Developer specializing in cloud microservices and healthcare interoperability
Senior QA Engineer specializing in game and interactive application testing
Junior Data Engineer specializing in cloud ETL/ELT and lakehouse platforms
Senior Full-Stack Software Engineer specializing in Python, React, and LLM-powered applications
Sai Krishna Sriram
Mid-level Generative AI & ML Engineer specializing in production LLM and RAG systems
“AI/ML engineer who shipped a production blood-test report understanding and personalized supplement recommendation product, using a LangGraph multi-agent pipeline on AWS serverless with OCR via Bedrock and RAG over vetted clinical research. Also built end-to-end recommender system pipelines at ASANTe using Airflow (ingestion, embeddings/features, training, registry, batch scoring/monitoring) with KPI reporting to Tableau, with a strong focus on safety, evaluation, and measurable reliability.”