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Vetted SQLAlchemy Professionals
Pre-screened and vetted.
Senior Full-Stack Engineer specializing in FinTech, Healthcare IT, and AI-enabled platforms
Senior Full-Stack Engineer specializing in cloud-native SaaS and healthcare platforms
Mid-level Full-Stack Software Engineer specializing in SaaS, AI/ML, and IoT
Mid-Level Software Developer specializing in .NET, APIs, and cloud-based enterprise systems
Junior Python Backend Developer specializing in AWS serverless APIs and ETL
Junior Machine Learning Engineer specializing in LLM fine-tuning and AWS deployment
Mid-level Python Backend Engineer specializing in Insurance APIs and Cloud Microservices
Mid-level AI/ML Engineer specializing in MLOps, LLMs, and computer vision
Mid-level ML Engineer specializing in MLOps, data engineering, and GenAI/RAG systems
Mid-Level Full-Stack Software Engineer specializing in cloud-native microservices
Mid-level Software Engineer specializing in cloud data platforms and microservices
Mid-level Software Engineer specializing in AI/GenAI and cloud-native backend systems
Senior Software Engineer specializing in cloud-native microservices and test automation
Senior Full-Stack Python Engineer specializing in SaaS, cloud, and microservices
Mid-Level Backend Software Engineer specializing in AWS microservices and AI/automation
Mid-Level Full-Stack Software Engineer specializing in cloud-native microservices and FinTech
Senior Python Backend Engineer specializing in scalable APIs, cloud microservices, and AI/ML platforms
Senior Full-Stack Software Engineer specializing in Python/Django and React/TypeScript
Ronald Forte
Entry-Level Software Engineer specializing in AI APIs and RAG systems
“Junior/entry-level AI/LLM engineer who built a production-oriented RAG onboarding and knowledge assistant that ingests GitHub repos and internal sources (e.g., Confluence/Jira) using ChromaDB, with reliability features like retrieval fallbacks, retries, caching, and monitoring. Currently implementing a LangGraph-based multi-agent workflow with intent routing and Pydantic/Magentic-validated structured outputs, plus CI/CD offline evals and online metrics (Grafana/Prometheus) to improve predictability and reliability.”