Vetted Agentic AI Professionals

“Product-minded frontend/UX leader with notable experience at CNBC, where they owned premium subscription and engagement flows from problem definition through production and post-launch iteration. They stand out for combining high-polish React implementation, Figma-driven systems thinking, and AI-assisted prototyping to quickly ship and refine conversion-focused experiences.”

“Built and shipped a production agentic LLM tool that helps internal teams update technical product whitepapers using plain-language edit requests, with strong guardrails (citations, verification, refusal/clarify flows) to reduce hallucinations and maintain compliance. Experienced taking LLM workflows from rapid LangChain prototypes to more predictable, debuggable LangGraph agent graphs, and orchestrating end-to-end ingestion/embedding/indexing/eval/deploy pipelines with Kubeflow.”

“Founder/idea lead behind InvantX, an AI-powered product helping people make better decisions with their own data. Developed the business model canvas and MVP plan, set up an early customer feedback loop, and iterates roadmap/architecture based on beta-user learning. Has participated in accelerators including FinAccelerate, Pegasus, and an NVIDIA program (AWS credits), and applies a metrics-driven, structured approach to traction building.”

Deepa Karunakaran

Screened

Senior Customer Success & Cloud Migration Leader specializing in AWS data and analytics

Cupertino, CA20y exp

“AWS enterprise customer leader supporting the Apple Maps account, focused on large-scale migrations from on-prem (e.g., Cloudera) to AWS EMR/EBS. Known for deep troubleshooting and cross-functional execution (Grafana-driven autoscaling fixes, Graviton capacity/ICE mitigation) and for tying roadmap alignment to commercial outcomes, including a cited $30M incremental ARR expansion.”

Nagsen Dahat

Screened

Executive engineering leader specializing in FinTech platforms and cloud-native systems

New York, NY18y exp

“Motivated by the desire to work independently after spending significant time working for others. Demonstrated notable discipline and follow-through by completing a Master's program with great grades while managing a full-time job, family with two children, and a social life.”

Jeremiah Medina

Screened

Senior AI/ML Engineer specializing in LLMs, RAG, and cloud-native MLOps

Orlando, FL11y exp

“Built and owned a real-time clinical AI assistant at Andor Health, taking it from prototype through deployment, monitoring, and iterative improvement. Brings strong healthcare-focused GenAI experience across RAG, hybrid retrieval, LoRA fine-tuning, and production Python services, with measurable gains in accuracy, speed, and reliability.”

“Senior data/AI and platform leader with Walmart- and T-Mobile-scale architecture experience, including building real-time inventory + forecasting platforms (Kafka/Cassandra/Hadoop) and Azure IoT systems. Known for translating board-level business goals into roadmaps that deliver measurable impact (e.g., $50M savings and $250M profit in a year; +2% conversion via Customer 360) and for hands-on problem solving in ML/forecasting (feature reduction and LASSO).”

“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.”

Dhruv Arora

Screened

Senior Generative AI Implementation Consultant specializing in RAG and agentic AI on cloud

Bay Area, CA3y exp

“LLM/RAG practitioner who built an AWS-based enterprise document search and summarization platform with RBAC and scaled it to 10K+ users, solving relevance issues via contextual chunking and hybrid retrieval. Also designed agentic workflows for a telecom forecast-validation use case using sub-agents, tool APIs, and strict context management, and has proven pre-sales influence (supported a $300K manufacturing deal with a roadmap-driven pitch).”

Johnny Davis

Screened

Senior Enterprise Customer Success Manager specializing in SaaS adoption and digital transformation

San Jose, CA18y exp

“Enterprise Customer Success leader (10+ years) with experience at Zscaler and supporting Fortune 500 customers, driving high adoption and renewals through metric-driven governance and executive stakeholder management. Known for cross-functional incident leadership (including coordinating with Apple and Product to ship a patch) and for enabling significant expansions (e.g., $600k+ add-on before renewal and a $750k DLP deal) while building Salesforce Marketing Cloud/CRM analytics and enablement tooling.”

“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.”

BHABANI Dash

Screened

Principal Enterprise Architect specializing in AI, cloud strategy, and digital transformation

Lake Villa, IL20y exp

“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.”

“Unity/C# gameplay engineer who has shipped a modular, data-driven combat ability system with strong measurable outcomes (≈80% fewer GC allocations, 15–20% better frame times, 10–12% higher early retention). Also integrated an LLM-driven NPC dialogue/quest hint system with a C#/.NET backend, caching/guardrails, and telemetry-driven iteration, and shipped Photon PUN real-time 4-player co-op plus a shared codebase across Meta Quest VR and iOS/Android.”