• Attend client meetings, map end-to-end business workflows, capture pain points & exceptions
• Draft structured action logs, deployment updates, demo materials and value proof documents
• Translate vague business demands into clear briefs for product & engineering teams
• Oversee UAT, resolve operational issues, drive smooth AI system adoption
• Inspect messy data (Excel, CSV, PDF, SharePoint files); write simple Python/SQL scripts
• Build reusable playbooks, templates and prompt workflows from deployment experience

• Strong written English; Mandarin preferred, Cantonese advantageous
• Basic Python scripting & SQL query skills, able to code without fully relying on AI
• Experience handling spreadsheets, unstructured documents and imperfect enterprise data
• Practical know-how of LLMs, AI agents, prompt engineering and their limitations
• Customer-centric, proactive follow-up, able to operate with loose requirements
• Background in implementation, technical BA, consulting, customer success or startup ops ideal
• No CS degree mandatory; self-taught practitioners with proven hands-on work welcome

• Familiar with Microsoft ecosystem: Teams, SharePoint, Azure, Fabric
• Industry exposure: Finance, procurement, supply chain, CPG, logistics
• Built automations, internal tools or AI workflows for live business users

• Focus solely on LLM fine-tuning, ML model research or technical algorithm work
• Prefer only creating strategy slides without hands-on delivery
• Avoid client engagements or see documentation/UAT as trivial tasks
• Over-depend on AI tools to mask weak foundational coding knowledge

• 30 days: Grasp product architecture, independently take meeting notes, audit raw data, run simple scripts
• 60 days: Own full follow-up for client deployments, prepare value validation materials, feed feedback to devs
• 90 days: Lead end-to-end small deployment cycles, confidently facilitate user sessions, scale repeatable processes

1. Intro call with founder Tim
2. Basic Python & SQL technical assessment (no AI allowed)
3. Take-home deployment case task
4. Solution debrief discussion
5. Paid trial project before permanent conversion

• Directly partner with founder at early-stage AI startup
• Own full client lifecycle from discovery to live launch
• Grow end-to-end startup operation capabilities
• Performance measured by tangible customer business value
• Shape company processes and standards as core founding team member

Email your CV + portfolio / sample work to [email protected] for application