Backend Engineer (Infrastructure & Platform) (f/m/d)

Zeit Ai · Munich

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TodayPosted · Aug 4
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Skills in this posting

Extracted from the posting text by the instrument — the demand side, read literally.

The posting

The opportunity

LLMs are changing analytical work. Capabilities that once required large teams of highly paid data engineers are becoming accessible to smaller companies for the first time. At Palantir, we delivered real data and BI value, but deployments never scaled without expensive, hands-on engineers. We believe LLMs change that, and we have the customers and revenue to prove the model works.

Now we scale and one key lever is the platform. Every new customer brings new data sources, more rows to sync, and more queries to serve. Your job is to make sure ZeitMind, our agent platform, can handle onboarding 10 new enterprise customers per week and the hard part isn't the compute.

It's capturing each business's context fast enough: connecting messy data systems, making sure the agent's answers are correct, that visualisations hold up, and that the customer is able to get value out of the product quickly. This is as much a product and correctness problem as an infrastructure one, and it hasn't been solved before.

Onboarding a customer should be boring. This is the role that lets everything else scale.

What you will do

Build the sync layer: millions of rows from ERP, CRM, and homegrown systems, ingested incrementally and reliably, without an engineer babysitting the pipeline

Cut onboarding time: connecting a new customer's data sources should take hours, not weeks. You abstract sources so our agents work with any of them the same way

Make the agent fast where it counts: speed comes from tool design that parallelizes, sub-agents, and branching, not tokens per second. You design tools so work can run concurrently and safely

Route data safely between customer networks and ours: security and reliability are features our customers pay for

Build the guardrails for correctness: automatic checks and integrated validation tooling so the agent's output can be trusted, and so it flags what a human should verify

Keep the platform simple: choose boring technology where boring wins, and be able to say why every system we run earns its place

You will thrive here if you

have built or scaled data platforms before and think clearly about data processing architectures

have a deep understanding of OLAP and OLTP systems and when to reach for each

bring strong backend experience with TypeScript and are at home in cloud infrastructure

get foundations right without overengineering them; you build for the scale we will hit next year, not for a hypothetical one

take full ownership from idea to production to impact, and are comfortable working without predefined specs

want to build foundations early rather than optimize mature systems

are genuinely interested in the data and agentic space and how LLMs enable new workflows for non-technical users

Requirements

You've been a lead architect or equivalent: built many systems yourself, and seen how large systems fail and evolve. You're here to learn from customers and take bets on a product that doesn't exist yet, not to learn how to write software.

Strong TypeScript and cloud infrastructure experience

English C1 or above; German a plus

What we offer

We are based in Munich and build the team around in-person work. We pay for your relocation.

Regular San Francisco offsites for product sprints and staying close to the frontier.

Zeit AI package: daily lunch allowance, free in-office dinner, wellpass membership, best tech & tools

You know someone? €5k referral bonus for every successful hire.

Tech stack

TypeScript end to end. Backend on Bun with Postgres and Supabase. React frontend (Mantine, TRPC, TanStack Query). Job/Process management, Docker, VPN/routing and Agentic frameworks: harness, tool calls, sandboxed tools, branching of data and specs.

About the interview process

First call with Elisa

Tech screening

Tech interview with Jonas

Decomposition interview

Second technical interview

Behavioural interview

Take-home case + Meet the team

References, offer

Apply

Still apply if you do not match every requirement. If you are exceptional in core areas and learn fast, we want to talk.

Compensation: €95K – €270K

  • Offers Equity
  • €5k referral bonus
  • total comp €95K – €270K
  • Offers Equity
  • €5k referral bonus

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