Lead Data Engineer (AI Systems)
Location: Munich, Germany
Working model: Hybrid, 3 days per week in office
Compensation: Up to €160,000 base salary + meaningful equity
Seniority: Senior / Lead / Founding-level
Can you build the data infrastructure underneath the AI product?
We are working with one of Munich's rising AI stars, who are building agentic AI solutions to change the Pharmaceutical and Life Sciences industry forever!
They aren't building yet another AI chatbot, their platform helps teams make sense of fragmented, messy and business-critical data, turning it into usable intelligence through AI-native workflows, automation and intelligent data infrastructure.
The company is now hiring a Lead Data Engineer, AI Systems to own the data layer that powers the product.
This is not a generic AI Engineer role. You will be joining early, working directly with the founders and technical leadership, and taking responsibility for the pipelines, infrastructure and validation systems that sit underneath the company’s AI workflows.
If you have built serious data pipelines before, understand orchestration and data quality deeply, and want to move closer to applied AI, this could be a strong fit.
What you will own
You will take responsibility for the design, build and scaling of data pipelines that support AI-driven products. This includes:
* Building robust ingestion, transformation and validation pipelines for complex enterprise data.
* Designing data infrastructure that can support LLM-powered extraction, automation and analysis.
* Working with fragmented, unstructured and semi-structured data from high-value business environments.
* Creating systems for data quality, evaluation, reliability and traceability.
* Collaborating closely with AI engineers, product teams and company leadership.
* Helping define the technical direction of the data function as the company scales.
* Supporting and later leading more junior engineers as the team grows.
What they are looking for
The strongest fit will be someone with a serious data engineering background who is excited by AI, rather than someone who has only built lightweight LLM applications.
Ideally you bring:
* Strong Python engineering experience.
* Proven experience building production-grade data pipelines.
* Good understanding of orchestration tools such as Dagster, Airflow, Prefect or similar.
* Experience with modern data tooling such as dbt, SQL, Postgres, data warehouses or data lakes.
* Strong understanding of data modelling, data quality and pipeline reliability.
* Experience working with messy, high-volume or business-critical data.
* Ability to work independently in a small, fast-moving technical team.
* Interest in AI systems, LLM workflows, RAG, extraction pipelines or intelligent automation.
Nice to haves
* Experience building data infrastructure for AI, ML or LLM products.
* Experience in regulated, sensitive or high-value data environments such as fintech, healthcare, pharma, insurance or B2B SaaS.
* Exposure to Docker, cloud infrastructure, Azure or similar.
* Experience mentoring junior engineers or growing a data engineering function.
* Previous startup or scale-up experience.
The Expectations
This is an early-stage company with a demanding technical culture.
They move quickly, set ambitious deadlines and expect people to take real ownership. This will suit someone who wants scope, speed and responsibility, rather than a narrow role inside a large corporate structure.
The company is office-first in Munich, with flexibility around exact working hours and hybrid working. Most of the team work a 7am-7pm or 9am-9pm stint every day.
They are not offering fully remote work, but they are open to people structuring their week around where they do their best work.
If this sounds like you, click apply or send your CV to me at s.cooper@cubiqrecruitment.com