About the role
Most CRM marketing still blasts generic messages at scale and calls it "personalization." Our founders experienced this firsthand in senior roles at HelloFresh, Salesforce, Uber, and others. Backed by top-tier VCs, they decided to build a better way.
Responsibilities, requirements, fit, evidence and preparation are organized here. The original posting stays available for final verification.
What you’ll do
- Own the technical customer journey from discovery through onboarding, pilot delivery, measured value, and scaled adoption
- Lead technical discovery before signature: understand how the customer makes money and which metric moves it, then validate the integration path, available data, measurement feasibility, and what the pilot can credibly promise
- Own onboarding: align stakeholders, define the data mapping and acceptance criteria, coordinate implementation, and take the customer live on its existing CRM stack
- Design and pre-register each customer experiment using Zelara's scientific standards: hypothesis, primary metric, cohort, control group, conversion window, success threshold, and decision rules, because a success bar set after seeing the data is not a result
- Own the customer-facing interpretation of results: reconcile Zelara's analysis with the customer's data, involve Science in novel or ambiguous analyses, and state clearly when the evidence is not decision-ready
- Enable the customer's team to operate campaigns independently rather than becoming the person who runs them
- Partner with the commercial lead on annual contracts, expansion, and renewal: identify the opportunity, quantify the value, and de-risk the technical plan
- Drive the product loop rather than report into it: turn recurring customer needs into product opportunities, engineering requirements, and research questions, and bring the evidence from live accounts that decides their priority
- Build what closes the gap in the meantime: use agents to produce the scripts, tooling, and prototypes that unblock an account before the platform covers it
What they’re looking for
Select a requirement to inspect fit, evidence or application context.
- You have led deployments, implementations, or technical accounts for mid-market or enterprise customers at a B2B SaaS company, and your work has influenced adoption, renewal, or expansion.
- You judge a customer's business before you design for it: which metric their leadership is measured on, which one is decoration, and what matters that nobody has said out loud. You aim the solution at the first.
- You can turn a business question into an analysis plan: define the right metric, cohort, and measurement window; identify what would disprove the claim; and judge whether the evidence is decision-ready.
- You have led real customer integrations and know that a successful import is not the same as usable data.
- You understand experiments: control groups, effect sizes, statistical power, conversion windows, and why the design has to be frozen before it runs.
- You know the lifecycle marketing stack (Braze, Bird, Iterable, Klaviyo, Customer.io, Emarsys, HubSpot): what it does well, where it stops, and how a CRM team works inside it.
- You are credible with a Head of CRM and their data engineer in the same hour, and you switch between them without losing either.
- You say the uncomfortable thing early, and a commitment with a date on it is a commitment.
- You want to build the function, not only perform the role.
- You are AI-native in how you work. A software engineering background is not a requirement. Building with agents is: the script that reshapes a customer's export, the prototype that shows a CRM team what we mean, the tooling that saves you the next ten hours.
- You are fluent in English. German is a strong advantage given our current market focus.
Helpful, not always essential
- You have been the operator on the other side, running lifecycle or CRM programs in-house, so you know what we are asking a customer's team to change.
- You have experience with experimentation platforms, bandits, or applied ML in production.
- You have converted pilots or POCs into multi-year contracts and can say what actually moved the decision.
How they work
- We are an AI-first team. We use spec-driven workflows and AI-assisted execution across engineering and go-to-market, adopting what makes us faster and discarding what does not. We value evidence, speed, and clear ownership over process theater, status reporting, or activity for its own sake.
- If you want to push the boundaries of how software gets delivered to customers, not just what gets delivered, you will fit right in.
How to apply
- You will own technical value realization for a portfolio of customers, from discovery and onboarding through live experiments, measured results, and scaled adoption.
- What You Will Do Own the technical customer journey from discovery through onboarding, pilot delivery, measured value, and scaled adoption Lead technical discovery before signature: understand how the customer makes money and which metric moves it, then validate the integration path, available data, measurement feasibility, and what the pilot can credibly promise Own onboarding: align stakeholders, define the data mapping and acceptance criteria, coordinate implementation, and take the customer live on its existing CRM stack Design and pre-register each customer experiment using Zelara's scientific standards: hypothesis, primary metric, cohort, control group, conversion window, success threshold, and decision rules, because a success bar set after seeing the data is not a result Own the customer-facing interpretation of results: reconcile Zelara's analysis with the customer's data, involve Science in novel or ambiguous analyses, and state clearly when the evidence is not decision-ready Enable the customer's team to operate campaigns independently rather than becoming the person who runs them Partner with the commercial lead on annual contracts, expansion, and renewal: identify the opportunity, quantify the value, and de-risk the technical plan Drive the product loop rather than report into it: turn recurring customer needs into product opportunities, engineering requirements, and research questions, and bring the evidence from live accounts that decides their priority Build what closes the gap in the meantime: use agents to produce the scripts, tooling, and prototypes that unblock an account before the platform covers it Your First 90 Days 30 Days (Immersion): Learn the platform and customer portfolio, join every active account, and take ownership of your first technical customer relationship.
- 90 Days (Scale): Own a small portfolio, deliver your first evidence-backed results readout, use it with the commercial lead to inform an annual-contract or expansion decision, and improve the playbook based on live accounts.
Benefits & working conditions
- Work alongside founders who have built and sold an AI-driven SaaS business and led large-scale B2C operations from the customer's side of the table.
- A founding senior individual-contributor role in Solutions Architecture. You define the playbook now, with a path to build and lead the function as the customer base grows.
- Autonomy over onboarding, pilots, and technical value realization, with close partnership on account growth and a tight working relationship with Product, Science, and Engineering.
- Direct access to real customers and real production data.
- Based in Berlin with regular travel to European customers.
- A competitive salary and a meaningful equity stake, early enough to shape the company's direction.
- Your choice of a Deutschlandticket or bike subscription, plus a gym/fitness club membership.
About Zelara.ai
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