Context64.ai
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Customer Engineering

Forward Deployed Engineer

Graz, AustriaFull-timeMid-Senior

You will work directly with engineering customers to turn fragmented enterprise data into usable context graphs, workflows, and AI-powered applications.

The role

Where engineering reality meets the context layer.

The Forward Deployed Engineer sits between customers, product, and engineering. The role turns real engineering data problems into deployed Context64 solutions.

You’ll be the person in the room when a Tier-1 OEM opens their PLM, CAD, ERP and simulation systems and asks what’s possible. You’ll write the entity model that fits their domain, configure the Data Context Hub to match their governance constraints, and ship the application surfaces engineers actually use day-to-day.

Inside the company, you’re the source of truth for what real engineering teams need next — the feedback loop from production back into platform direction.

Responsibilities

A week in the role.

Work with customers to understand engineering data landscapes — sources, ownership, governance constraints, current pain.
Configure DCH models, workflows, and graph structures that fit each domain — automotive, manufacturing, energy, pharma.
Build application surfaces on top of context graphs: explorers, builder UIs, embedded agent interfaces.
Collaborate with product and engineering teams to ship platform features the next customer will need too.
Support pilots from discovery to production — onboarding, acceptance, governance sign-off.
Translate customer requirements into product feedback that ends up on the roadmap, not in a deck.
What we look for

What makes someone great in this role.

Strong engineering and systems thinking. You see the structure under the surface and can describe it.
Production experience with React, TypeScript, Python, APIs, or data systems — at least two of those, in real environments.
Ability to understand complex enterprise data environments quickly enough to be useful in the first month.
Clear communication with technical and non-technical stakeholders.
Ownership mindset. You see a gap, you close it — without waiting for permission or process.
Comfort working in early-stage product environments where some of the road is still being paved.
What you’ll work on

Real context infrastructure.

DCHM4AIC64 StudioEngineering AI workflowsKnowledge graphsEnterprise systems

Doesn’t disqualify you if missing — but helps.

  • Knowledge graphs, semantic data, or Neo4j experience.
  • Direct work with PLM, ALM, ERP, CAD, or requirements systems.
  • AI agents, LLM workflows, retrieval architectures.
  • Automotive, aerospace, industrial, or systems engineering background.
  • German language skills (B2+) — most customers operate in EU/DACH.
Why join

What this role actually offers.

Build infrastructure, not demos

Production systems running inside the customer perimeter — engineering AI that stays useful after the launch deck closes.

Work close to customers

The product team sits one channel away. Your customer signal moves the roadmap inside the same week.

Shape a young platform

DCH and M4AI are still defining their primitives. The structural calls you make now compound for years.

Solve hard context problems

Graph design, governance, retrieval, and agent reasoning over engineering ground truth — at real scale.

Apply

Apply for this role.

Hiring contact: Jan Bernasch · Chief Operating Officer · Hiring contact

Attach your CV in your reply email, or include a link above.

Or email careers@c64.ai

Not the right role, but the right mission?