Vetted Artificial Intelligence Professionals

“Hands-on IT/engineering executive who has led high-impact architecture changes and compliance-driven data systems. Notably built an internally developed columnar database at Troparé (with dual-support UI for legacy/new DBs) and shipped an MVP in 3–4 months with dramatic performance improvements, and previously delivered PCI/opt-out compliant deletion workflows while addressing DB performance and migrations.”

“Operations and agile enablement leader currently shaping internal operations at KlariVis (rapidly growing, founder-led company). Implemented Scrum, quarterly planning, cross-functional ways of working, executive dashboards, and org-wide training while also improving release management, bug prioritization, and go-to-market workflows; blends strategic structure with hands-on execution and change adoption through iterative feedback.”

“Implementation/project management leader with experience in Weight Watchers' business solutions division managing ~44 strategic client accounts across marketing, tech, business ops, and executive leadership. As Director of Project Management at Tier One Solutions Group, proactively implemented Microsoft Project to improve executive visibility and deadline adherence; brings a leadership psychology lens to driving clarity, accountability, and discretion as a Chief of Staff-style partner.”

“Robotics software engineer with deep ROS2 Humble/Nav2 experience who built an SDF-based navigation system (RRT* global planning + gradient-based local avoidance) and implemented scan-matching localization. Proven real-time performance debugging and optimization on hardware (Unitree B1), including halving compute-cycle latency and resolving ROS2 jitter/message-drop issues through explicit QoS and executor/callback-group design.”

“AI engineer who built a production e-commerce system that analyzes product images alongside sales and demographic data to generate actionable creative recommendations, now used by 20+ clients. Also built orchestrated document/agent pipelines (Airflow, LangGraph) including a compliance drift detector auditing 401 compliance documents, with an emphasis on traceability, logging, and production integration.”

“Repeat early-stage startup CTO/first engineer who helped take Vettery from 0 to a $100M+ exit. Led product-oriented engineering with heavy investment in data science/ML, including a recommendations system and candidate evaluation model (90%+ predictive effectiveness), and scaled the modeling stack using parallel processing and Apache Airflow.”

“Built and deployed an LLM/RAG system that uses differential privacy and distributional similarity checks to transform private data into a non-sensitive knowledge base while preserving utility. Also has experience demonstrating adversarial ML concepts (FGSM) to non-technical audiences by focusing on observable model behavior rather than implementation details.”

“Built and productionized an AI agent-based in-app assistant at ISAFE to guide users through document workflows, piloting with a partner school district and then rolling out across districts. Combines hands-on LLM/agent debugging (logs, fallback rates, state/context tracking) with strong technical demos and sales enablement through live workflows and pilot programs (e.g., Osceola School District).”

“ML/AI practitioner in healthcare (Syneos Health) who has deployed production clinical NLP and risk models. Built a BERT-based physician-note information extraction system on Docker + AWS SageMaker (reported ~42% retrieval improvement) and automated retraining/deployment with Airflow and drift detection, while partnering closely with clinicians to drive adoption (reported ~18% readmission reduction).”

“Software engineer with experience spanning an SEL internship and Walmart, combining backend/data pipeline work (Python, Kafka, relational DBs) with DevOps practices (Docker, Grafana, GitHub/Jenkins CI/CD, GitOps). Notably contributed to a REST-to-GraphQL migration aimed at reducing cloud utilization and implemented testing strategies to validate the transition.”

“Robotics-focused engineer from a senior capstone who built the backend motion-control software for a semi-autonomous line-following vehicle split across two ESP32s. Experienced in ROS 2 (DDS, lifecycle nodes, QoS) and in bridging microcontroller telemetry to a laptop ROS 2 stack over UART with custom structured protocols, using Gazebo simulation to tune PID and validate behavior before deploying to hardware.”

“Data/NLP practitioner with experience in both financial services (Truist) and government (USDA), including an NLP-driven analysis of EU regulations to anticipate US regulatory focus and a major redesign/cleaning of complex pathogen lab-test public datasets. Built production data-quality pipelines with Dagster, Pandera, and Azure Synapse, and is comfortable validating hypotheses with historical backtesting and SME-driven quality controls.”

“UE5 C++ gameplay programmer who has built core gameplay frameworks (characters, AI, abilities, inventory/interaction, dialogue, weapons, save) and shipped on Steam (Zone 13). Demonstrated strong profiling and optimization skills by using Unreal Insights to diagnose CPU frametime spikes and removing visible hitching with a custom C++ object manager, plus experience with replicated systems using GAS and Fast Array Serialization.”

“Game/technical designer with live-service ownership at Wargaming (World of Tanks) driving KPI-based monthly events and engagement loops via data-informed reward tuning. Recently shipped Batman Arkham Shadow by automating a narrative pipeline that converted script-graph dialogue into a string library, cutting weeks of work down to hours under aggressive deadlines. Experienced rapid prototyping in UE4 (including AI-driven mode logic) and cross-functional alignment practices.”

“Cross-functional product/engineering leader with startup and enterprise experience (Whimstay, Wells Fargo, Leap AI Technologies). Has owned end-to-end delivery including UI and payment architecture—built a multi-customer reservation payment flow using pre-auth plus event/timer-driven reminders and handled tricky edge cases like date changeover. Also introduced lightweight process (Jira, sprints, team/module structuring) to increase delivery speed in an early-stage AI document-matching startup.”