Vetted Generative AI Professionals

“Engineering/technology leader with experience at Expedia and startup OneRail, known for building business-aligned technology roadmaps and scaling orgs rapidly (11 to 120 engineers in a year). Has driven large productivity and efficiency gains by operationalizing AI agents (code reviews, upgrades, security fixes) and implementing ChatOps-based deployment architecture, using data-driven experimentation to manage platform changes and conversion impacts.”

“AI/LLM engineer who built and productionized an internal RAG-based knowledge system that ingests diverse sources (PDFs, Markdown, Slack), scaled retrieval with distributed FAISS and parallel ingestion, and reduced hallucinations via re-ranking, grounding prompts, and post-generation validation. Also has hands-on orchestration experience with Airflow and Kubernetes for reliable ETL/model pipelines, monitoring, and staged rollouts; reports ~15% accuracy improvement and adoption as the primary internal knowledge tool.”

“Entrepreneurially driven technical leader seeking to partner with a founder/business plan owner to provide technical expertise. Helped drive Wiser's expansion into Europe by evaluating acquisition targets' technical estates and making the recommendation that was chosen. Applied lean, high-leverage product thinking at Nabis on a two-sided marketplace, delivering buyer value with a simple algorithm and later adding paid boosting for brands.”

“Enterprise technology executive (CRO/GM/CEO) with 27+ years as a P&L owner across major global services providers (IBM, Unisys, Virtusa, Cognizant). Recently led a metrics-driven turnaround as CEO of Mastech Infotrellis after integrating three acquisitions and rebuilding GTM. Now exploring an AI Governance/Compliance/Risk-focused venture, potentially via acquiring and reorienting an existing governance business toward AI.”

“Built and deployed a production LLM-powered RAG document intelligence system used by non-technical enterprise stakeholders, cutting document search time by 40%+ while improving answer consistency. Demonstrates strong MLOps/data workflow orchestration (Airflow, AWS Step Functions, managed schedulers across GCP/Azure) and a metrics-driven approach to reliability, evaluation, and cost/latency optimization with guardrails and observability.”

“Aspiring AI product builder interested in LLMs and deep learning, exploring forming a team (including fresh graduates) and leveraging crowdsourcing to develop ideas. Has not raised capital and has no VC/accelerator experience yet, but is thinking ahead about funding needs and partnering with an operational co-founder while potentially joining an existing team.”

“Data science/NLP practitioner with experience at NVIDIA and Microsoft building production-grade NLP and data-linking systems. Has delivered high-performing pipelines (e.g., F1 0.92) and large-scale entity resolution (F1 0.89), plus semantic search using embeddings and Pinecone with ~30–40% relevance gains, backed by rigorous validation (A/B tests, ROUGE, MRR) and strong MLOps/workflow tooling (Airflow, Databricks, FastAPI, MLflow, Prometheus/ELK).”