The role
The independent automotive aftermarket runs on data. But that data sits in silos, locked inside each company. The value of connecting it is obvious to everyone. What’s missing is the infrastructure that makes sharing it safe. Kyvera exists to build it. And infrastructure for shared data is only as good as the data flowing through it: mapped, matched, enriched, and quality-assured at a scale no human team can deliver. That is your job.
As Lead AI Engineer, you build the intelligence of the Kyvera data space. You embed applied AI into real partner use cases: data quality, semantic understanding, enrichment, matching, automation, and insight generation. You work with existing models, tools, and services wherever they create measurable value, and you build what the market cannot buy.
AI at Kyvera is not a research lab, a parallel innovation track, or a feature showcase. AI is use-case embedded: it ships only when it improves measurable partner outcomes and passes governance, auditability, and stop-gate criteria. You will set that bar, and you will hold it.
This is a founding role, and a hands-on one. You design, you build, you operate, and you answer for what your systems do in production.
What you’ll do
- Design, implement, and operate applied AI services within the Kyvera data space: anomaly detection, data enrichment, normalisation, automated quality checks, semantic linking, matching, and insight generation.
- Translate concrete partner and platform use cases into AI-enabled features with clear success metrics, evaluation criteria, and production-readiness requirements.
- Build robust evaluation, monitoring, and feedback loops for every AI component: quality measurement, drift detection, failure analysis, human review points, and rollback mechanisms.
- Own the intelligence layer end-to-end: how data is understood, mapped, matched, and quality-assured across the data space. The Platform Lead owns what the platform technically is and how it runs. Where the two meet, the boundary is explicit; where they collide, the CTO decides.
- Make AI components auditable and explainable, and work closely with the Governance Lead so that machine-made decisions meet Kyvera’s data sovereignty, compliance, and trust principles by design.
- Support the first live partner use cases with measurable AI-driven improvements in data quality, interoperability, operational efficiency, or insight generation.
- Keep exploring what is becoming possible, while keeping a clean line between production-critical capabilities and experiments.
The AI delivery guardrail
AI at Kyvera only moves forward when it creates measurable value for a real use case. Every AI initiative starts with a clear hypothesis, a success metric, and a risk assessment, and it must pass defined stop-gates on its way from prototype to pilot to production. If an AI feature does not improve the use case, cannot be monitored reliably, creates unacceptable risk, or lacks a safe fallback, it does not ship.
Who you are
- You have deep hands-on experience in applied machine learning and AI engineering, and you have carried AI systems into production and kept them there.
- You have turned AI and ML capabilities into production services, workflows, APIs, and data pipelines, and you know the distance between a convincing demo and a system partners rely on.
- You have a strong practical command of modern AI methods: model selection and integration, embeddings, retrieval, classification, enrichment, evaluation, and monitoring.
- You design AI around measurable business and data outcomes, never technology for technology’s sake.
- You take production seriously: observability, testing, failure handling, explainability, human-in-the-loop workflows, and rollback strategies are part of your definition of done.
- You move fast while holding a high bar for quality, trust, compliance, and operational reliability.
- Experience with data-heavy, B2B, or regulated environments, entity resolution, knowledge graphs, retrieval-augmented generation, or large-scale data pipelines makes you stronger in this role.
- You work fluently in English; German is a plus.
What this role offers
A founding seat in an institution the industry has talked about for years and never built. You shape the applied AI layer of new market infrastructure from day one: not by building research demos, but by shipping trusted, measurable, production-grade intelligence into real industry workflows. What you build here decides how an entire market experiences what shared data can do.
You work as part of a small founding team, report directly to the CTO, and operate with founder-level ownership, backed by TecAlliance’s three decades of automotive data expertise, trusted neutrality, and industry relationships.