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Vetted Prompt Engineering Professionals
Pre-screened and vetted.
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
Senior Software Engineer specializing in AI/ML, search, and scalable cloud platforms
Mid AI/ML Engineer specializing in LLMs, RAG, and multimodal systems
Senior Machine Learning Scientist specializing in LLMs, RAG, and health AI
Director-level engineering leader specializing in AI platforms and consumer applications
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.”
Alejandra Cuin
Senior Venture & AI Strategy Consultant specializing in investing, portfolio ops, and ecosystem building
“Venture investing/sourcing professional with experience at L'Attitude running high-volume founder sourcing across tools (Harmonic) and ecosystem channels (accelerators, hackathons, Discord, university labs). Demonstrated ability to turn cold outreach and early relationships into diligence and investment committee discussions, while maintaining a rigorous CRM-driven pipeline process and long-term founder nurturing through consistent value-add.”
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.”
Bocheng Wan
Mid-level Software Engineer specializing in consumer robotics and machine learning
“Developer with a structured AI-assisted coding workflow centered on algorithmic rigor, type-safe scaffolding, and spec-driven modular design. Used Claude Code to help build an Android SDK for IPC, quickly ramping up on AIDL and compressing delivery including unit tests from several weeks to two weeks.”
Shashikant Sreenivasaiah
Executive software engineer and founder specializing in AI, robotics, and cloud systems
“AI-native engineer who says 100% of current development is done through coding agents and reports roughly 10x productivity gains. Currently building 'AI TV,' a production video-generation system with multi-agent orchestration, including a motion-graphics pipeline where agents handle high-level design, low-level implementation, and iterative review. Particularly strong in designing codebases and workflows so AI systems can effectively use architectural and product context.”
Tina Bai
Executive operator-founder specializing in GTM, revenue strategy, and AI-native commercial operations
“Operator with Deloitte consulting experience supporting PE/VC-backed portfolio companies and current experience inside a VC-funded Series C scale-up. Building a bootstrapped D2C women’s telehealth brand (Petty Pills) with two initial SKUs, deployed tech stack, and white-labeled clinical/compliance infrastructure, leveraging AI tooling to keep operations lean while focusing on full-time operator roles.”
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.”
Vinay Ramrupe
Mid AI/ML Engineer specializing in LLM and enterprise generative AI
“ML/AI engineer focused on taking LLM systems from experimentation to reliable production, including enterprise copilot and RAG-based knowledge retrieval use cases. Stands out for combining data pipelines, model training, inference optimization, automated evaluation, and safety guardrails, with cited impact including 20% throughput gains and 30% less manual evaluation effort.”
Ashwin Puthige
Engineering Manager specializing in full-stack web platforms, payments, and AI features
“Hands-on engineering manager on a large web product who built an AI-driven navigation search and led a major post-acquisition unification effort across 3 companies and 5–7 teams, including front-end architecture for 60+ developers. Also owns a high-scale BFF (800 endpoints) and drove a deep reliability fix involving Kubernetes/Envoy/Redis session bloat, adding monitoring and preventative controls.”
VP Software Engineering Manager specializing in full-stack platforms, data, and AI in FinTech
Senior Software Engineer specializing in ML, search, and AI-powered backend systems