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Vetted Compliance Professionals
Pre-screened and vetted.
John Clarke
Executive Finance & Strategy Leader specializing in Big Tech and capital allocation
“Operations/finance leader who joined Google during a rapid growth phase (circa 2007–2008) and built foundational analytics and governance systems across revenue, partnerships, and global marketing finance. Known for shifting organizations from qualitative/"feel" decisions to metrics-driven quota setting, deal evaluation (including cannibalization and margin thresholds), and ROI-based marketing budgeting while aligning senior stakeholders like CFO and CMO.”
Christopher McLean
Executive engineering leader specializing in security, privacy, and high-scale infrastructure
“Veteran operator from top-tier tech companies including PayPal, LinkedIn, Stripe, Facebook, and Merge, now seeking the right startup idea to found. Brings hands-on angel investing experience across 5 startups in the EU and US plus additional exposure through X-Stripe Angels, giving them both operator and investor perspective.”
Senior Backend Engineer specializing in AWS cloud-native systems and data workflows
Executive technology architect specializing in cloud platforms, SRE, and enterprise SaaS
Senior Software Engineer specializing in AI platforms, payments, and consumer systems
Senior AI/ML Engineer specializing in LLM applications, RAG systems, and MLOps
Jesse Olson
Executive AI technology leader specializing in agentic AI and enterprise transformation
“Candidate is exploring a startup in the autonomous agentic AI space and is approaching it with a disciplined founder mindset. They are evaluating market opportunity, competition, customer pain, ROI, technical feasibility, and MVP options while already speaking with potential customers across verticals to validate needs and buying processes.”
Patrick Hovakimian
Executive Legal Leader specializing in government investigations, white collar defense, and governance
Neeraj Sharma
Executive Engineering Leader specializing in AI/ML platforms and cloud-scale distributed systems
“Senior engineering/technology leader with experience driving board-backed, multi-year platform transformations in retail commerce (American Eagle) and scaling ML/product delivery platforms at Amazon Alexa. Known for data-driven build-vs-buy decisions, org scaling (6→80), and measurable outcomes including 98.5%→99.9% uptime, 234 experiments generating ~$200M revenue lift, and increasing delivery velocity from 1.5 to 30 features/week while transitioning to DNN/large-model architectures.”
Summer Guo
Executive Venture Capital Investor specializing in AI, robotics, and energy infrastructure
“Clean energy founder (Ishan "Summer") who built an energy storage/battery materials venture in 2022 focused on data centers and factories, raising $10M split between venture capital and government funding. Demonstrates end-to-end venture execution: multi-year market observation, team formation, customer/market validation, research collaboration, prototyping, and channel-partner-led go-to-market.”
Pradeep Nadella
Mid-level AI/ML Engineer specializing in LLM optimization and real-time fraud/risk modeling
“ML engineer with 5 years at Stripe building and productionizing real-time fraud detection at massive scale (3M+ transactions/day; $5B+ annual payment volume). Delivered measurable impact (22% accuracy lift, 18% loss reduction, +3–5% authorization rates) and has strong MLOps/orchestration experience (Docker, Kubernetes, Airflow, MLflow, CI/CD, monitoring/rollback) plus a structured approach to LLM agent/RAG evaluation.”
Executive Operations & Program Management Leader specializing in Legal Ops and Tech
Executive general manager and CEO specializing in SaaS, e-commerce, and marketplaces
Executive investment and fintech leader specializing in data analytics and wealth solutions
Senior AI/ML Engineer specializing in Generative AI, RAG, and MLOps for FinTech
Principal Data Scientist specializing in Generative AI and security analytics
Senior Full-Stack Software Engineer specializing in AI/ML for FinTech & E-commerce
Ridhi Singhal
Mid-level strategy and analytics professional specializing in growth and due diligence
“Growth and launch operator with Uber experience spanning marketplace expansion, rider/driver activation, and scalable onboarding systems in new-city launches, including Uber Shuttle in India. Stands out for combining data analysis, operational modeling, and cross-functional experimentation to unlock incremental revenue, improve NPS, and build repeatable playbooks that scaled across markets.”
Bill Schlageter
Executive CIO and transformation leader in global ERP, modernization, and M&A integration
“Board member/advisor to a mid–$10M revenue company aiming for $100M+, focused on portfolio trimming, analyst-quadrant positioning (Gartner/Forrester/ISG), and building scalable commercial operations. Has driven org redesign (separating marketing and sales), CRM rollout (Salesforce) alongside existing Dynamics accounting, and coaches founders to adopt metrics, messaging discipline, and delegation for global scale.”
Tolulope Akinlabi
Mid-level Cyber & Cloud Security Analyst specializing in AI/ML and cloud risk
“Built a production AI security compliance assessment system using the OpenAI API that ingests company policy documents, performs RAG over embeddings stored in Supabase/FAISS, and generates executive-level gap and maturity reports mapped to NIST CSF, SOC 2, and PCI DSS. Also developed a multi-agent trading assistant orchestrated with LangChain, combining live market data (Yahoo/Polygon.io), sentiment/technical indicators, LSTM-based forecasting, and LLM-generated recommendations.”
Jayaprakash Majji
Mid-level AI/ML Engineer specializing in LLM fine-tuning, RAG, and scalable inference
“ML/LLM engineer who built and shipped an LLM-powered internal knowledge assistant at Meta, focusing on production-grade RAG to reduce hallucinations and improve trust. Deep experience with scaling and serving (FSDP/DeepSpeed/LoRA, Triton, Kubernetes autoscaling) and reliability practices (Airflow retraining, MLflow versioning, monitoring with rollback), including sub-100ms latency and ~35% GPU memory reduction.”