Forward Deployed Strategist

We’re hiring a Forward Deployed Strategist to put our AI agents to work inside healthcare organizations. Most of your time goes to designing and deploying agentic workflows with customers. The rest goes to turning what you learn into product. You have a CS or similarly quantitative background, think in systems, understand how LLMs actually behave, and love working with customers.

About Clicks
Our mission is to accelerate the world’s transition to autonomous operations. We’re starting with healthcare revenue cycle management. We build AI agents that do anything from prior auth to denial management and payment posting, working in the same EHRs, payer portals and phone calls that billing teams use today. Customers get 90%+ of the work fully automated, go live in under 5 weeks, and are guaranteed 50%+ cost savings.

Why now: payers use AI to deny claims, and providers who don’t fight back with AI fall behind. Billing teams also churn because the work is repetitive. Our agents take that work off their plate.

• Investors: Y Combinator, 20VC, Fly Ventures, Yellow. $4.5M raised.
• Team: Small, technical, founder-led. You work directly with the founders.

The Role
You own deployments end to end: learn how a customer’s team does the work today, translate it into logic our agents follow reliably, prove it works, and take it live.

Let’s be direct: this is mostly deployment work. If you mainly want to own a roadmap, this isn’t the role. If you want to learn what to build by doing the work with customers, it is. At an AI agent company, the people who know what to build are the ones who deployed it. Deployment is the path into product here, not a toll you pay before it.

You don’t need to write production code. You do need to be exceptionally sharp at logic, able to reason about where an LLM will succeed or fail, and able to earn the trust of a revenue cycle director in the first meeting.

What You’ll Do

Deploy agentic workflows (~80%)

• Run customer kickoffs and map workflows like prior auth, eligibility, denial management and payment posting, down to every step and every exception.
• Turn SOPs into agent instructions, decision logic and escalation rules.
• Evaluate agents on historical cases, run supervised pilots with the customer’s team, then roll out incrementally.
• Debug production failures: figure out whether it’s the instructions, a missing rule, a portal quirk or a model limitation, then fix it or drive it with engineering.
• Track automation rate, accuracy and cost per workflow, and present results to customer leadership to drive expansion.

Shape the product (~20%)

• Spot what repeats across deployments and turn one-off fixes into reusable product: templates, tooling, evals.
• Work side by side with engineering to cut time-to-live and effort per workflow.
• Bring the customer’s reality into every product decision.

Who You Are

Required

• Degree in Computer Science, Mathematics, Physics, Engineering or another quantitative field.
• New grad to 2 years of work experience. This role is built for early-career people.
• You genuinely enjoy working with customers, including the unglamorous parts. You’ve done tedious work to get a result and it didn’t bother you.
• Customer-facing experience of any kind: consulting or client internships, founding something, sales, teaching.
• You understand LLMs beyond the hype: context, prompting, tool use, evals, and where models break.
• Exceptional structured thinking. You turn messy processes into clear logic.
• Comfortable reading code, logs and JSON, even though you won’t write production code.

Nice to have

• You’ve built with LLMs: side projects, agents, prompt pipelines, evals.
• Exposure to healthcare, revenue cycle or other operations-heavy industries.

Interview Process

1. Intro call (15 min) with Dominik, our CEO. We get to know each other and talk about what drew you to the role.
2. Deployment case (take-home, about 1 hour, plus a 30 min call). We send you a realistic RCM workflow, like a prior auth SOP with a few portal screenshots. You write the instructions our agent would follow and flag where you expect it to fail. Use any AI tools you like, just tell us how you used them. On the call, you walk us through your work and we throw in a few new edge cases. No coding needed. We’re looking at your logic, your LLM intuition and how you explain your thinking.
3. Call with our Head of Deployments (45 min). A deep dive into how we run deployments, what great looks like in this role, and your questions about the day-to-day.
4. In-person trial day in our SF office. You work on a real deployment task alongside the team and see what the job is actually like.