Pre-screened and vetted.
Intern AI/Data Science Engineer specializing in LLM agents, data engineering, and predictive analytics
Senior Customer Success Manager specializing in Enterprise B2B SaaS and global renewals/expansion
Mid-level Full-Stack Developer specializing in AWS, Python/FastAPI, and React
Executive Biotech Founder/CEO specializing in industrial biotech and food tech commercialization
Senior AI/ML Engineer specializing in Generative AI and Computer Vision
Executive Operator (Founder/COO) across Consumer Beverage and Early-Stage Tech
Senior Strategy & Operations leader specializing in healthcare and pharmacy growth
Principal Data Scientist specializing in AI/ML forecasting and MLOps
Senior AI/ML Engineer specializing in LLMs and enterprise conversational AI
Senior Customer Success Manager specializing in Enterprise SaaS and Ad Measurement
Junior Data Engineer specializing in Azure data platforms and GenAI analytics
“Data/ML practitioner with experience spanning medical imaging (retinal vessel analysis for hypertension/CVD risk prediction) and enterprise data engineering at Carl Zeiss. Built large-scale SAP data cleaning/validation pipelines (10M+ daily records, ~99% accuracy) and RAG-based semantic search with LangChain/vector DBs that cut manual querying by 82%, plus automation that reduced data onboarding from 8 hours to 12 minutes.”
Senior Talent Acquisition & Recruiting Operations Partner specializing in hiring analytics
“Recruiting leader in the agency/media space (Omnicom/Hearts & Science and WPP Media) who manages a small recruiter pod and builds operational systems to improve hiring outcomes. Known for process standardization and change management (Greenhouse templates, SLAs, automation) and for measurable stakeholder impact—e.g., cutting hiring manager response lag to 48 hours and partnering with a CFO to prioritize/stagger hiring based on capacity and budget.”
Executive HR Leader specializing in talent management, total rewards, and DEIB
“HR/People Operations leader with experience standing up core HR infrastructure at startups, including implementing ADP Workforce Now and Lever plus workforce planning and recruiting strategy frameworks. Known for pragmatic operational diagnostics (interviews/SOP review), change management, and measurable impact—e.g., creating budget discipline for a graduate development program and driving $100K+ in savings while improving goal alignment, development planning, and recruiting efficiency.”
Executive AI Architect specializing in enterprise cloud and FinTech solutions
“Candidate brings an operator-to-founder profile with leadership experience in IT and Business Systems and a strong grasp of how ideas become venture-backable products. They speak fluently about startup evaluation criteria such as TAM, technical defensibility, speed to scale, and AI differentiation, and appear especially motivated by building solutions end-to-end in startup or venture studio environments.”
Mid-level Supply Chain Planner/Buyer specializing in sourcing, MRP, and analytics
“Supply chain/sourcing professional focused on semiconductor tooling NPI ramp-ups, owning vendor selection through production and delivery. Demonstrates strong cost and trade-risk mitigation (e.g., avoided 25% Section 301 tariff via HTS/landed-cost analysis) and measurable supplier performance turnarounds (OTD improved to 95%) using SAP MRP, shortage analysis, and structured supplier governance.”
Mid-level Data Engineer specializing in experimentation, analytics, and AI-driven product experiences
“Built production LLM automations using the Claude API, including a sales enablement workflow that summarizes playbooks and incorporates sales call metadata into strategic one-pagers. Experienced in orchestrating and scheduling data pipelines with SnapLogic, Airflow, and Databricks, and in scaling LLM API calls via parallel/batch processing. Also partnered with HR to deliver prompt-tuned, automated Slack messaging aligned to business tone and acceptance criteria.”
Mid-level Supply Chain Analyst specializing in logistics optimization and planning analytics
“Supply chain/procurement professional (Maersk) who leads end-to-end freight sourcing initiatives using heavy analytics (SAP/SQL/Python/Excel) to drive measurable savings. Known for automating sourcing workflows (60% faster bid evaluation) and building Power BI dashboards to monitor contract compliance and supplier performance post-implementation.”
Mid-level SaaS Account Executive specializing in renewals, expansion, and named accounts
“Quota-carrying SaaS seller with experience at Splunk and Everlaw, spanning security/observability and legal tech. Strong in self-sourcing (events + outbound), running full-cycle deals ($50K–$75K ACV), and winning competitively via ROI/TCO narratives while navigating security/compliance and legal/procurement. Has also helped build a repeatable GTM motion in a high-ambiguity segment by refining ICP, messaging, and sales process rigor (MEDDICC, Gong, CRM hygiene).”
Director-level Program & Professional Services Leader specializing in Enterprise SaaS and PMO
“Entrepreneur who invested in a startup franchise concept and opened a dog-grooming store that became the most successful location in company history within one year, with projected revenue of $600K+ in 2026. Uses structured market sizing (PAM/TAM) and GTM thinking, and has executed cost-effective local marketing through grassroots social and community sponsorships.”
Executive Client Partner specializing in engineering and digital services
“Founder building an agentic AI-based low-code platform for B2B enterprise applications, validated through enterprise client conversations and delivered via rapid paid MVP/POCs. Platform has seen production traction (6–7 apps, 1000+ daily users) and includes capabilities like QR scanning integrated with ERP/PLM systems. Experienced in business development and client relationships, with a pragmatic, ROI- and speed-focused approach to product and GTM under tight capital constraints.”
Executive Applications Development & Analytics Leader specializing in enterprise transformation
“Candidate has prior startup experience building systems and has firsthand experience with a venture that lost angel funding. They show thoughtful reflection on why the startup failed—emphasizing unclear success criteria, weak funding planning, and lack of team consensus—and would seek experienced advisors earlier in future ventures.”