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Vetted OpenAI API Professionals
Pre-screened and vetted.
Mid-level Solutions Engineer specializing in enterprise integrations and healthcare IT
Mid-level AI Engineer specializing in LLMs, RAG chatbots, and cloud AI testing
Mid-Level Software Engineer specializing in AI, cloud-native microservices, and full-stack systems
Staff Machine Learning Engineer specializing in Generative AI, MLOps, and Computer Vision
Principal AI Platform Architect specializing in agentic AI and enterprise LLM infrastructure
Mid-level AI/ML Engineer specializing in GenAI, MLOps, and big data on cloud platforms
Senior Infrastructure Platform Architect specializing in hybrid cloud and Kubernetes automation
Junior Software Engineer specializing in AI, distributed systems, and recommendation systems
Senior Machine Learning Engineer specializing in computer vision and healthcare AI
Mid-level Software Engineer specializing in AI platforms and backend systems
Senior Full-Stack Engineer specializing in event-driven systems for FinTech and Healthcare
Executive AI Engineering Leader specializing in research-to-production LLM systems
Senior AI/ML Engineer specializing in Generative AI and conversational systems
Principal Full-Stack Engineer specializing in AI platforms and enterprise systems
Mid-level Generative AI Engineer specializing in LLMs, NLP, and multimodal systems
Devisri Veeramachaneni
Senior Software Engineer specializing in cloud backend systems and LLM-powered agents
“Amazon Fire TV Devices engineer who built and shipped a production LLM-powered lab triage and validation system that grounds recommendations in internal runbooks/known-issue data and pushes evidence-based actions via dashboards and Slack. Emphasizes safety and measurability with structured JSON outputs, replay-based evaluation on historical incidents, and production metrics (e.g., disagreement rate and time-to-first-action), plus cost/latency optimizations like caching, batching, and rule-based fast paths.”
Varshith Dupati
Mid-level Software Engineer specializing in AWS, full-stack development, and AI data systems
“Backend engineer who built a Python-based data profiling/statistics platform processing up to 50M rows and ~300 metrics, using a DAG execution model, multithreading, and smart caching to cut processing time by up to 70%. Also improved PostgreSQL query performance from 12s to 2s via indexing/query rewrites, integrated an LLM (LangChain + OpenAI) for explainable “chat with the pipeline” functionality, and designed an AWS EC2+SQS architecture for scalable, isolated per-user processing.”