Investment Manager – AI, Early Stage

Role Overview

• Source and win AI investments
• Build a sourcing engine for AI-native companies across ANZ and selectively globally. That means developing real relationships in the AI community: researchers, builders, operators, open-source contributors. We have processes in place and a high performing team to learn how to do this effectively.
• Be the first call for founders building in AI. Get involved in the community by showing up at the right events, contribute to the discourse, and earn trust before a round opens.
• Run Investment Committee-quality diligence
• Evaluate technical defensibility: can this be replicated by a frontier model update? Is the data moat real? What does the competitive landscape actually look like?
• Assess founding teams with depth: their technical credibility, their commercial instinct, their ability to recruit. You will be learning how to do this from some of the best Investors in the region.
• Write investment memos that are rigorous on the technology, honest about the risks, and clear on why now.
• Help build Airtree's AI capability
• We're building AI-powered tools internally: for sourcing signals, company research, meeting preparation, and portfolio monitoring. You will contribute to this as a builder, not just a user.
• Help the team develop sharper frameworks for evaluating AI companies, staying current on what's emerging from the labs and what it means for our portfolio.
• Support portfolio founders
• Be a useful sounding board for portfolio companies navigating AI adoption, integration, and strategy.
• Connect founders to relevant people in your network: talent, customers, co-investors, technical advisors.

Requirements

• We're less interested in years of experience than in what you've actually done. The right person might come from VC, might come from building an AI company, might come from a research lab.
• You build things. You've shipped products, tools, or prototypes using AI. You don't just talk about models — you use them, break them, and understand their limits from first-hand experience.
• You follow the research. You read papers, track what's coming out of the major labs, and can form a view on what's signal and what's noise. You know the difference between a novel architecture and a fine-tuned wrapper.
• You're deeply networked in AI. Or you have the instinct and energy to become so, fast. You can build trust with a PhD researcher as easily as with a commercial co-founder. You're comfortable in rooms where you're the least technical person and rooms where you're the most commercial one.
• You're high agency. You don't wait to be told what to do. You see a gap, you fill it. You find the company before anyone's heard of it. You build the tool the team didn't know it needed.
• You can write a compelling investment memo. Clear thinking, honest risk assessment, a point of view on why a company will win. You don't need to have written one before, but have strong written communication.
• You care about founders. You understand that behind every deal is a person making the hardest decisions of their career, and you want to be genuinely useful to them.
• Nice to have (but not required):
• Prior venture capital or startup operating experience.
• A technical background: computer science, engineering, maths, or self-taught equivalent.
• Experience evaluating deep-tech or frontier-technology companies.
• An existing network in the ANZ or global AI community.
• A public body of work: writing, open-source contributions, talks, or products people can point to.

Benefits

• 5 weeks of leave: 4 weeks annual leave plus 1 bonus week of lifestyle and wellbeing leave.
• Hybrid work environment
• 16 weeks of paid parental leave, plus a flexible return to work program.
• An annual budget for your training & self-development.
• A range of health and wellness benefits including EAP, mental health first aid training, skin checks, flu vaccines and more.