Vetted Keras Professionals

“Full-stack and AI product engineer with strong accessibility and voice-interface experience in senior living, building systems for older adults where trust and usability are critical. Has shipped React/TypeScript and .NET MAUI products, productionized Azure OpenAI features, built RAG-based research tools, and improved both product outcomes and technical performance with measurable impact.”

Aditya Niture

Screened

Mid-level Full-Stack Software Engineer specializing in AI-augmented web and mobile systems

Chicago, IL4y exp

“Builder-oriented engineer who has shipped production systems across fintech-style payments, mental health recommendations, industrial oil-and-gas analytics, and AI-assisted client discovery. Stands out for combining deep backend reliability practices with founder-facing product scoping, and reports using Claude-based internal tooling to increase delivery capacity by 40% and handle eight concurrent projects.”

“Full-stack engineer with experience building a NASA-funded simulation management platform using React, TypeScript, Next.js, PostgreSQL, AWS, and Docker. Stands out for owning complex, long-running workflow features end to end in production and driving measurable performance improvements, including a 40% database load reduction and API latency improvements from roughly 500ms to under 200ms through Redis caching and async architecture.”

“ML/AI engineer with hands-on experience building healthcare and fraud-detection systems from experimentation through deployment, monitoring, and retraining. Stands out for combining real-time IoT pipelines, cloud-native MLOps, and GenAI/RAG in regulated healthcare settings, with reported impact including reduced emergency response times and a 25% reduction in manual diagnosis time.”

Kathan Patel

Screened

Mid-level Generative AI Developer specializing in Python and LLM applications

5y exp

“Currently working on Kavia AI, an end-to-end AI coding platform that lets users generate enterprise applications from prompts and existing codebases via SCM integrations. The candidate has hands-on experience across the GenAI stack—prompt engineering, LangGraph-based multi-agent orchestration, RAG, knowledge graphs, FastAPI, and AWS monitoring—with a focus on making software creation accessible to non-technical users.”