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Vetted Prompt Engineering Professionals
Pre-screened and vetted.
Intern Software Engineer specializing in data engineering and LLM evaluation
Senior Applied Scientist specializing in LLMs, GenAI systems, and AutoML
Senior Applied ML Scientist specializing in LLMs, ads ranking, and RAG systems
Senior Strategy & Operations Leader specializing in AI and data-driven transformation
Staff Full-Stack & AI Engineer specializing in LLM platforms and scalable cloud systems
Mid-level Machine Learning Engineer specializing in LLM personalization and scalable MLOps
Senior Full-Stack Engineer specializing in scalable cloud platforms and AI integrations
Mid-level AI/ML Engineer specializing in LLM fine-tuning, RAG, and MLOps
Senior Full-Stack Engineer specializing in AI/GenAI and cloud-native platforms
Mid-level Machine Learning Engineer specializing in real-time recommender systems and MLOps
Intern Machine Learning Engineer specializing in LLM systems and recommendation/search
Mid-level AI/ML Engineer specializing in LLMs, RAG, and multi-agent systems
Mid-level AI/ML Engineer specializing in NLP, computer vision, and recommender systems
Peter Gluck
Principal Software Engineer specializing in scalable, secure multi-platform systems
“Engineering leader and former CTO/Disney|ABC engineering manager who built white-label mobile app architecture that supported a branded app and successful exit, and later scaled Disney Channel brand app teams across iOS/Android/web and major OTT platforms. Led kid-safety architecture for DisneyNOW (“Junior mode” with PIN) and partnered with product/legal on COPPA compliance, emphasizing maintainable tech choices and strong execution processes.”
Brian Sanders
Senior Backend Engineer specializing in GenAI, LLMs, and scalable data pipelines
“Backend/ML platform engineer from Snapsheet who owned production Python services and data pipelines for insurance claims, including an AI document classification/summarization FastAPI service on ECS/Fargate processing 1M+ documents/year. Strong in AWS infrastructure (Terraform, CI/CD, secrets/IAM, autoscaling), Glue/PySpark ETL with schema evolution controls, and legacy SAS-to-microservices modernization with safe, feature-flagged rollouts and measurable performance wins.”
Harish Kasu
Mid-level AI/ML Engineer specializing in Generative AI, RAG, and MLOps
“AI/LLM engineer with production experience at NVIDIA and Microsoft, including building a RAG-based enterprise knowledge assistant that improved accuracy by 42% and scaled to thousands of queries. Deep in inference optimization (TensorRT-LLM, Triton, quantization, speculative decoding) and MLOps/observability (Prometheus/Grafana, MLflow, LangSmith), plus orchestration with Kubeflow/Airflow across multi-cloud.”
Yishi Wang
Junior Machine Learning & Data Science professional specializing in LLMs and analytics
“Amazon internship experience building production GenAI analytics for the returns organization: a multi-agent LLM+RAG system that let analysts query multiple heterogeneous data sources in natural language without hand-written SQL. Also built and operationalized four Apache Airflow DAGs for large-scale ETL, emphasizing observability and freshness-aware metadata to keep outputs accurate and up to date.”
Mid-Level Software Engineer specializing in distributed backend systems and cloud microservices
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and scalable GPU inference