Build Internal AI Agent Teams
Design and deploy AI agents that handle operational work across portfolio companies — including customer support (Tier 1 & 2), SDR and sales outreach, onboarding automation, content workflows, and engineering maintenance
Automate core business processes: CRM updates, document processing, reporting, and analytics pipelines
Work directly with portfolio company operators to identify the highest-value automation opportunities
Measure impact in hours of labor replaced, team output increased, or cost savings generated

Build External AI Products

Develop new AI-powered products such as vertical voice agents, AI copilots, workflow automation tools, and AI documentation systems tailored to vertical markets
Own the product from prototype through launch, including reaching first paying customers
Integrate AI capabilities with existing systems: CRM, ERP, internal tools, SaaS platforms, and third-party APIs
Build agentic workflows including multi-agent coordination, decision engines, and tool-using AI agents

Ship and Iterate

Move fast from idea to MVP to production — bias toward working software over documentation
Run beta tests with real users, gather feedback, and improve continuously
Optimize AI agent performance: latency, cost, accuracy, and human intervention rate
Ensure production reliability through monitoring, evaluation, and model lifecycle management
Collaborate cross-functionally with product, engineering, and go-to-market teams

What This Role Is Not

Not a research or proof-of-concept role — everything you build ships to real users
Not a traditional backend or systems engineering role focused on ticket execution
Not bound by story points, sprint rituals, or rigid SDLC stages
Not limited to internal tooling — what you build may become a product customers pay for

Proven track record of building products, tools, automations, or side projects that went live and created real impact
Strong working knowledge of AI and machine learning tools, large language models (LLMs), and agent frameworks
Ability to go from zero to functional prototype quickly
Comfort with ambiguity — you will often be defining the problem as much as the solution
Bias toward action over planning

Technical Skills

Hands-on experience with LLM integrations, RAG architecture, and prompt engineering
Proficiency with workflow orchestration and automation platforms (e.g. n8n, Zapier, Make, LangChain, CrewAI)
Ability to build and maintain API integrations across CRM, ERP, and SaaS systems
Understanding of vector databases, embedding pipelines, and model hosting
Strong debugging and problem-solving skills across full AI system stacks

Mindset & Approach

Outcome-oriented: you measure success in labor hours saved, revenue generated, and adoption rate — not tickets closed
Strong operational intuition — ability to understand a business workflow and identify where AI creates the most leverage
Comfortable working directly with business operators, not just engineering teams
Ability to reason about AI system limitations, failure modes, and appropriate human-in-the-loop design

AI Automation, Agent Builder

Key skills