AI Operations Associate

Kaizen Equity Partners•Scottsdale, AZ

2d•Hybrid

About The Position

This is a forward-deployed role: you will sit with deal teams, not in a back office. As an AI Operations Associate, you will help drive a top M&A bank's rapid shift from traditional, hands-on operations to agentic ones, with always-on AI agents assisting the firm's core processes. You will shape our technology stack: the models and tools our agents use, and the integrations and controls that make them safe to run on live deals. You will shadow teams across the firm to learn how the work really gets done, pinpoint the problems worth solving, and build the solutions. You will decide what can be automated and where the firm should invest more of its people's time. Central to the job is a single judgment call, made over and over: what is intelligence an agent can carry, and what is judgment a banker must own? As opportunities arise, you will also bring the same rigor to some of our portfolio companies' biggest challenges. If you are an analytical early-career professional who wants to be at the front of applied AI, this role gives you real impact now and a clear path to seasoned AI product expertise at the intersection of financial services and technology.

Requirements

AI fluency. You use AI tools every day, push them hard, and know where they fall short. Built an agent, an automation, or a scrappy side project? We want to see it.
0–3 years of experience with an analytical, technical, or business background.
Structured problem solving. You map out the ways to solve a problem, weigh the trade-offs, and land on a clear recommendation. You pick up new processes quickly and in depth, capture the steps experts take for granted, and have the grit to see hard problems through.
Clear, structured writing. Playbooks and write-ups are a big part of the role.
Attention to detail and pride in producing high-quality work.
Team orientation. You are sociable and hardworking, and you want to grow into AI product management.

Nice To Haves

Experience in software, technology, consulting, investment banking, or financial services
A degree in software engineering, business, accounting, or finance
Basic coding ability
Data analytics skills: strong Excel, familiarity with Power BI or similar tools, and the ability to turn data into clear visualizations

Responsibilities

Learn the business & the tech. Shadow deal teams, operations, and finance work to find the problems worth solving and where work bottlenecks. Collect real examples, document the rules and exceptions, and draw a clear line between intelligence agents can handle and judgment that stays with bankers.
Design agentic systems. Model each process as a cross-functional system of agents: which agents it needs, what each one owns, the playbooks they follow, what starts a run, and where a person must approve. Build in auditability, cost control, repeatability, and data security from the start.
Diagnose and improve. Review run logs, outputs, and agent transcripts; refine playbooks, model choices, and approval points. Run evals, track accuracy, cost, and turnaround for every squad.
Shape the product. Write up platform improvements backed by evidence from real runs, and work with product and engineering to scope and test them. Identify the tools and features that would unblock the highest-value work.
Train and support the team. Onboard bankers and staff onto each squad, be their first call when an output looks off, and build and maintain the documentation that keeps every squad running without you in the room.
Collaborate. Work closely with partners, deal teams, and engineering in a fast-paced, entrepreneurial environment.