• Learning support that makes an impact: You assist our participants with hands-on AI projects and serve as the first point of contact for questions — empathetic, solution-oriented and patient. • Motivator & structure provider: You help overcome learning barriers, boost participants’ confidence, and provide guidance in their daily learning routines — even when topics like prompt engineering, LLMs or AI-powered automation initially seem complex. • Foster understanding rather than lecture: You explain AI concepts in a practical, easy-to-understand way, support transfer tasks and encourage direct application in the professional context — e.g., when working with tools such as ChatGPT, Claude, Gemini, Make or Zapier. • Teamwork with instructors: You provide feedback from the learning experience and help ensure our programs continuously improve. • Help shape processes: You actively participate in weekly team calls and contribute to further developing the quality of our programs.

We're a Germany-based company in the trading of industrial equipment and spare parts space. We've got our processes and SOPs clearly figured out on paper and now we are looking for someone tech-savvy to help us bring them to life digitally. We're looking for a freelancer who really knows their way around SmartSuite (or Monday.com) to help us build a smooth, automated, and easy-to-use workspace. What we need help with: Building the system: Translating our written SOPs into a highly organized, trackable workspace in SmartSuite. Automating the boring stuff: Setting up internal automations for routine tasks. Keeping it clean: Structuring the database so it's logical, scalable, and our team actually wants to use it. Who we're looking for: You have hands-on experience building out relational databases and workflows in SmartSuite (Monday.com or Airtable experience is good, too!). You understand business logic—you're a system builder, not just doing data entry. Bonus points: You've worked with supply chain, logistics, or similar business frameworks before.

• Partner with senior and C‑Suite stakeholders to identify “agent‑first” opportunities across business units and define multi‑phase AI Workforce roadmaps tied to clear business outcomes. • Lead the design of complex, production‑grade agentic systems using Snowflake Intelligence (no‑code/low‑code) and Cortex Search/Analyst, emphasizing configuration and semantic modeling over custom code. • Design multi‑step “Reasoning & Acting” (ReAct) flows using Snowflake’s UI, semantic layers, and native apps to orchestrate tools, policies, and data workflows. • Architect high‑accuracy retrieval‑augmented generation (RAG) and knowledge solutions using Cortex Search, with patterns for content onboarding, relevance tuning, evaluation, and continuous improvement. • Advise on necessary Snowflake Horizon policies and related governance capabilities to ensure agents are secure, auditable, and compliant with client and industry standards. • Lead the most complex, ambiguous Snowflake AI engagements from discovery through production, acting as the escalation point and “safety net” for critical Snowflake Intelligence accounts. • Develop phData‑wide blueprints, reference architectures, playbooks, guardrail templates, and ROI frameworks for Snowflake Intelligence–based agent deployments. • Mentor Consultants and Senior Consultants, modeling how to own projects end‑to‑end and effectively engage executive stakeholders, while evangelizing LCNC agentic patterns across the practice. • Partner with Sales and Solutions Engineering to scope complex AI Workforce opportunities, contribute to proposals, and help grow existing accounts by identifying “what’s next” for AI Workforce.

• Lead AI ecosystem assessments; identify maturity gaps and design tailored governance frameworks (principles, policies, decision-rights) aligned to client's industry, regulatory environment, and AI enablement vision • Own multi-workstream engagements; drive executive alignment and multi-year governance roadmaps connected to AI strategy and value realization • Define governance evaluation and approval processes for AI tools and use cases: risk tiers, scoring methodology, and control expectations by risk tier • Develop AI governance operating model blueprints: governing bodies, roles, RACIs, and interaction models across Technology, Product, InfoSec, Risk, and Legal • Define and operationalize AI FinOps guardrails, including: spend visibility, budget thresholds, usage policies, platform/tool approval, license rationalization, and TCO decisions integrated into the broader governance model • Facilitate executive and working sessions to align stakeholders and drive decisions • Define governance metrics and dashboards tracking value, cost, risk exposure, control coverage, and governance effectiveness • Recommend third-party AI governance tools; collaborate with engineering teams to ensure implementability on modern data & AI platforms • Shape and close strategic opportunities in partnership with sales: value propositions, solution approaches, and delivery models • Represent phData externally as a thought leader on AI governance at conferences, webinars, and partner events