Vetted Generative AI Professionals

“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.”

Tricia Biggio

Screened

Executive media and creative-tech leader specializing in entertainment and AI storytelling

Los Angeles, CA18y exp

“Former co-founder/CEO of a venture-backed media-tech startup who spent 6 years raising capital, leading through market shifts, and building with major investor backing. She brings strong relationships across venture studios and senior executives in media, entertainment, consumer products, startups, and AI, and led her last company into Amazon's AWS GENAI accelerator as one of 15 selected in North America.”

“Engineering leader who built and delivered an IoT smart-spaces platform for the self-storage and smart-living domains, translating customer requirements into architecture, capability maps, and a multi-milestone roadmap. Personally stood up missing AI/ML capabilities (including churn prediction) using Databricks (Delta Lake/MLflow), enabling follow-on features like energy optimization and security/anomaly detection. Scaled an org from 20 to 80+ with disciplined Agile planning (Jira Advanced Roadmaps/Confluence) and strong executive/customer-facing leadership during high-stakes customer commitments.”

Parth Vadera

Screened

Senior AI/ML Data Scientist specializing in recommender systems, LLMs, and MLOps

Tracy, CA11y exp

“ML/NLP leader with 12+ years of impact across LinkedIn, TikTok, and Levi's, building and productionizing multimodal recommendation and embedding-based search systems. Deep experience in entity resolution, vector retrieval, and rigorous evaluation, with cloud-native deployment/monitoring (MLflow, Airflow, SageMaker/Lambda, Azure ML, Kubernetes) and demonstrated double-digit relevance gains at millions-of-users scale.”

Raymond Otero

Screened

Director of Customer Experience & Success specializing in regulated cloud and agentic AI transformation

Philadelphia, PA28y exp

“Founder of a self-funded side advisory (e-Regency Advisory Services LLC) focused on helping early- and growth-stage technology companies improve customer experience, modernize cloud platforms, and build customer success/operations strategies leveraging AI. Has worked closely with founders and startup leadership teams and has supported companies as they prepared for or pursued funding, bringing a pragmatic, operationally disciplined approach to validating and scaling new ideas.”

Shant Mardigian

Screened

Executive Engineering Leader specializing in scalable streaming, media supply chain, and AI operations

19y exp

“Tech executive with Disney experience who has repeatedly scaled and restructured engineering organizations (from 4 to 30 and up to 100+), using OKRs/KPIs to drive business-aligned roadmaps. Hands-on with architecture and platform strategy, including adopting MongoDB Atlas to centralize transactional data and building shared core services (security/permissions, auditing, compliance) to increase product velocity across distributed teams.”

Alexander Schaab

Screened

Executive Technology & Product Leader specializing in ADAS and software-defined vehicles

Cupertino, CA14y exp

“Automotive technology leader who has driven ADAS/autonomous driving (L2++ to L4) and AI-assistance roadmaps for Mercedes and Volkswagen Group. In current role, built a software-defined vehicle organization from a handful of people to ~150 supporting VW, Porsche, and Audi, while setting scalable architecture foundations across brands and vehicle classes.”

Jean-Marc Chanoine

Screened

Executive sales leader specializing in Enterprise SaaS and AI go-to-market

New York, NY15y exp

“Self-funded aspiring founder with a few million dollars available to launch a consumer health product startup centered on oxymetazoline nasal spray and AI-driven marketing. He claims deep familiarity with venture/accelerator ecosystems, was accepted by Fractal, and serves as an advisor at Berkeley SkyDeck, suggesting strong startup-network access and ecosystem fluency.”

“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.”

“Engineering/product leader with repeated experience defining roadmaps and delivering platform migrations across SaaS and enterprise contexts. Scaled an education system from two districts to 2M+ students statewide, and led an Elasticsearch-based architecture for an internal Disney product serving ~100K employees. Known for rigorous execution (RAID/OKRs/sprints), strong stakeholder communication (weekly AI summaries), and empowering teams via end-to-end ownership and customer-connected development.”

“Operator focused on scaling and growing organizations, with experience in PE/VC-backed environments. Familiar with PE/VC and accelerator/studio models and how to apply them to create business agility and rapid experimentation while preserving innovation as companies scale.”

Yishi Wang

Screened

Junior Machine Learning & Data Science professional specializing in LLMs and analytics

Chicago, IL3y exp

“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

Screened

Mid AI/ML Engineer specializing in LLM and enterprise generative AI

San Francisco, CA5y exp

“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.”