Vetted Artificial Intelligence Professionals

Cia Hang

Screened

Executive IT and Operations leader specializing in digital transformation and security

Chicago, IL13y exp

“Candidate is very familiar with the venture capital and broader investment landscape, but is not interested in founding a company. They have worked with several TPG-backed or TPG-owned organizations, helping drive business scaling, cost reduction, and execution against investor governance requirements.”

“Education strategy and product leader with deep math education expertise who helped transform a literacy/assessment-focused company into a more comprehensive, integrated math solutions provider. Particularly strong at embedding AI-driven insights into teacher workflows in a human-centered way, balancing personalization, usability, teacher autonomy, and educational equity.”

“Product leader with experience modernizing and merging complex B2B platforms in industrial, facilities, and logistics contexts. Notably led the integration of Smartbin and WasteForce into a single Contelligent platform with no customer attrition, and has shipped AI-informed IoT products that made building optimization more accessible to non-analytical users.”

“Long-tenured EdTech operator who joined LinkIt! as the third Data Analyst when the company had fewer than 40 employees and grew into a Data Quality Manager over 7+ years. Stands out for blending data operations leadership—ETL migration, reporting automation, process documentation, and training—with highly hands-on startup execution across office operations, hybrid work rollout, and crisis response during COVID.”

“Software engineer with experience spanning high-scale backend systems and distributed consensus: led a 6-person team delivering a production data querying/visualization platform with major latency improvements via cursor-based pagination and streamed results. Built a RAFT-based distributed logging tool resilient to partitions and storage constraints, and at Nasuni developed FastAPI services processing multi-terabyte workloads for 500+ enterprise customers with secure API key management.”

“Enterprise Customer Success leader in fleet/telematics who managed a multi-million ARR portfolio through complex post-acquisition platform migrations and a large-scale 3G-to-4G transition. Uses data-driven health scoring, QBRs, and stakeholder alignment to drive adoption, reduce churn risk, and support renewals/expansion, and has influenced product roadmap via customer-driven reporting enhancements.”

Hritvik Gupta

Screened

Mid-level AI Engineer specializing in LLMs, RAG, and healthcare AI

San Francisco, CA3y exp

“Built and scaled an AI-powered voice/chat patient engagement platform at Penn Medicine from early prototype into production clinical workflows, focusing on latency, edge cases, and user trust. Strong in LLM reliability engineering (structured prompts, validation/fallbacks), real-time troubleshooting with observability, and cross-functional enablement through pilots, demos, and sales/customer partnership.”

“Early-stage product engineer who has shipped an AI-assisted workflow web app end-to-end, spanning Next.js/TypeScript frontend, Python-backed LLM APIs, Postgres analytics, and async backend workflows. Strong ownership after launch as well, including usage tracking, prompt and UX iteration, latency reduction, and measurable database performance improvements.”

“Analytics professional at Optum with hands-on experience turning messy healthcare claims data from SQL, Excel, and CRM systems into validated reporting datasets and Power BI dashboards. They also built reproducible Python workflows for claims analysis and owned an end-to-end project focused on improving claims processing efficiency through metric design, segmentation, and stakeholder-driven operational improvements.”

Ben Coats

Screened

Executive technology leader specializing in startups, SaaS, and cloud-native platforms

Newport, VT24y exp

“Early-stage technical advisor working fractionally with an AI health tech startup focused on autism therapy, helping turn a functional prototype into a deployable enterprise application. Brings a mix of hands-on coding, infrastructure/Terraform experience, and founder-oriented thinking around market opportunity, studio fit, and right-to-win.”

“Entry-level software engineer who independently built an AI-powered feedback aggregation and analytics dashboard end-to-end using Cloudflare Workers, D1, and React. Stands out for combining serverless backend design, LLM-based categorization, and thoughtful UI/UX polish, with a practical approach to production debugging and data reliability.”

“Built a production, real-time clinical documentation system at HCA that converts doctor–patient conversations into structured clinical summaries using speech-to-text, LLM summarization, and RAG. Demonstrated measurable gains from medical-domain fine-tuning (clinical concept recall +18%, ROUGE-L 0.62 to 0.74) while meeting HIPAA constraints via PHI anonymization and encryption, and deployed via Docker/FastAPI with CI/CD and monitoring.”

“Software engineer currently building AI-powered backend systems for interview analysis, with end-to-end ownership of an LLM-based monitoring platform. Stands out for combining practical product delivery in an ambiguous early-stage environment with measurable impact: over 40% reduction in manual review effort and roughly 20% lower inference cost.”

Robert Gardunia

Screened

Staff Full-Stack Engineer specializing in AI systems architecture

Gig Harbor, WA20y exp

“Veteran developer with 30 years of experience building unusually ambitious AI and full-stack systems, including a civic project tracker for the city of Casa Grande and multiple patent-pending AI architectures. Particularly strong in multi-LLM orchestration, agentic error-correction, and lightweight 3D/avatar experiences, with a track record of turning ambiguous ideas into working production prototypes quickly.”

“Graduate student researcher on the EARTH project (college collaboration with Moog) working on robotics for an arm/bucket system. Implemented waypoint-based path planning, built an Apriltag data pipeline, and developed ROS 2 tooling including a joystick-to-DeltaCAN teleop node; exploring reinforcement learning policies trained from Tera simulator + ROS 2 bag data to optimize trajectory planning under varying pressure/load conditions.”

“Built a production multimodal LLM-based vendor risk assessment platform that ingests SOC reports and other documents, uses a strict RAG pipeline with grounded evidence (page/paragraph citations), and dramatically reduces analyst review time. Experienced with LangGraph/LangChain/AutoGen for stateful, fault-tolerant agent workflows, and emphasizes reliability (schema validation, guardrails) plus low-latency delivery (~1–2s) through hybrid retrieval, reranking, caching, and model tiering.”

“Operations-focused advisor/operator who helps early-stage and scaling companies create alignment and execution rigor through OKRs, integrated tool stacks (Asana/Slack/HubSpot/Salesforce), and KPI/BI dashboards. Notably improved a mid-sized e-commerce company’s order fulfillment efficiency by 30% by automating data flow between sales and logistics via an integrated inventory management system, and mentors non-ops founders using a 'Translate–Simplify–Empower' model.”

“Cloud/Kubernetes-focused engineer with production ownership in multi-account AWS environments (GE) and EKS-based platforms (Lumeus.ai). Strong in incident response and reliability—diagnosed IAM-driven serverless failures (SQS/Lambda) and Kubernetes deployment issues (CrashLoopBackOff, memory pressure) with rollbacks, policy fixes, and improved monitoring. Built secure Jenkins CI/CD and delivered infrastructure via CloudFormation and Terraform for serverless and EKS stacks.”

“Enterprise Customer Success leader with experience at Wellfound (AngelList Talent) and Doximity, owning strategic accounts end-to-end and driving adoption through structured onboarding, QBRs, and analytics. Notably secured Wellfound’s largest renewal (Zoox) and co-developed a white-glove recruiting service at Doximity that scaled to 40 customers and produced $1M in revenue in its first year.”

“Unity/C# gameplay engineer with 3.5 years leading Scraptics at Halfbrick, owning and shipping the game’s core inventory puzzle loop (200+ interacting items) with strong stability and player-positive design fixes. Proven mobile optimization impact (sub-20 FPS/overheating to 60 FPS) and Photon PUN multiplayer experience from game jam and capstone projects; actively designing LLM-driven swarm AI architecture using Claude with async calls, caching, and fallbacks.”

João Barbosa

Screened

Junior Computer Science Engineer specializing in AI-driven game dialogue systems

Oeiras, Portugal4y exp

“Unity generalist who has shipped a solo VR tangram game for Meta Quest, handling everything from asset art to mechanics and multi-level logic. Built an original 2D top-down pixel-art game (“Mental Twist”) combining campus exploration with puzzle-based courses and a time/HP/XP-driven progression and grading system; prefers structured production environments and is currently seeking a 9-to-5 schedule.”

Vansh Amara

Screened

Junior Software Engineer specializing in AI systems and robotics infrastructure

Madison, WI1y exp

“Robotics software engineer with hands-on ROS 2 experience building real-time perception/control infrastructure and multi-sensor fusion (radar/ultrasonic + GNSS/IMU) with deterministic latency and safety fallbacks. Debugged rover navigation drift via rosbag replay and timing analysis, improving state estimation by gating GNSS and switching to SLAM when GPS degraded. Also brings strong distributed-systems and build/CI tooling experience (gRPC/Protobuf, Docker, Bazel cross-compilation for ARM/RISC-V, GitHub Actions).”

Gabriel Hatewa

Screened

Senior Customer Success Engineer specializing in SaaS and FinTech client solutions

San Francisco, CA8y exp

“AppSec-focused customer-facing practitioner with Worldpay experience advising clients on fraud reduction via stronger transaction validation and monitoring, translating technical controls into quantified business risk to secure buy-in. Has quickly learned and supported SonarQube in production by integrating it into CI/CD and guiding remediation, and has implemented security integrations in Kubernetes with secrets management and observability while resolving RBAC/network policy issues.”