Hard technical problems
Work on graph systems, agent memory, data integration, and enterprise AI — at the layer that determines whether any of it actually works in production.
Careers
Build the context layer for engineering AI.
We're building the systems that help engineering teams connect knowledge, reason over context, and deploy AI safely into real workflows.
Why join
Mission-driven, deeply technical.
Work on real engineering AI problems
Build graph-native systems
Work close to customers and product
Small team, high ownership
Enterprise-grade technical challenges
Open roles
1 open role.
Don't see your role? We're always open to strong builders.
Send us your profileHiring process
Clear, fast, no theatre.
01Intro call
A short conversation about you, the role, and what you’re looking for.
02Technical / product discussion
A deeper dive into how you think and build — no trick puzzles.
03Team conversation
Meet the people you’d work with day-to-day.
04Offer / collaboration plan
Full compensation breakdown and a clear plan to start.
Do work that becomes infrastructure.
If you build systems that matter, we should talk.
Careers · Now hiring·Graz · Hybrid
Build the context layer for engineering AI.
Join a team building graph-native AI infrastructure for complex engineering environments — where context, traceability, and systems thinking matter.
01Mission · why we exist
We work on the layer between enterprise engineering systems and AI.
Context64.ai connects fragmented engineering data, models it as governed context, and makes it usable by AI agents, applications, and engineering teams.
It's infrastructure work. The people who join us care about the structure under the surface — how engineering reality maps to a graph, how that graph stays trustworthy at scale, and how AI gets the same kind of structured understanding our best engineers already have.
01 · Intake
Source connections
Native connectors and ingestion agents across PLM, CAD, ERP, simulation, document stores.
02 · Context
The governed knowledge graph
Data Context Hub — ontology, graph, governance, retrieval. The structural core.
03 · Delivery
Production AI agents & applications
Memory 4 Your AI and C64 Studio — agents, workflows and UIs that engineers actually use.
02Why join · what you sign up for
Four reasons engineers and operators choose this.
We're not pitching foosball or perks. The work itself is the offer — what you get to spend your week on, who you get to spend it with, and what shows up in production at the end of it.
Real customer environments
Build for engineering teams working on complex physical products — automotive, manufacturing, energy, pharma. Not toy demos, not benchmark theater.
Small team, high ownership
Your work directly shapes the product, the architecture, and what customers ship. No layers between your decisions and the result.
Research-to-production culture
Turn deep engineering concepts into usable products deployed in real environments. We ship; we don’t write papers.
03Open roles · apply directly
Open positions.
1 role· updated weeklyDept
04Hiring · what to expect
How we hire.
Four conversations. About a week of total clock time, two to three weeks of calendar time. No take-home traps, no surprise rounds.
01
Intro call
30 minutes with a founder. Your background, what you’re looking for, what we’re actually building.
~ 30 min02
Role / technical discussion
A working session with the role lead. Real problem, your thinking out loud, not pop-quiz code.
~ 75 min03
Team conversation
Meet 2–3 of the people you’d work alongside. Both directions — we want you to interview us too.
~ 90 min04
Offer
Written offer with full Austria-compliant comp disclosure, equity, start date, and a single point of contact.
Within 48hOpen application
Don't see the right role?
We're always interested in people who understand engineering systems, AI, graphs, enterprise software, or customer delivery. Send a short note and your work — we read everything.