Crebiliti
AI Systems Architect

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About Crebiliti
Crebiliti is developing a new category of enterprise AI assurance technology. Rather than asking organisations to trust AI outputs, Crebiliti provides transparent evidence retrieval, provenance, explainable reasoning and auditable decision support for high-consequence environments. The platform is designed for regulated industries, government and enterprise customers where understanding why an AI reached a conclusion is as important as the conclusion itself. A provisional patent has been filed covering key aspects of the technology and the platform is now entering its pilot development phase.
The Opportunity
We are seeking exceptional AI Systems Architects to join a small, highly capable engineering team building the first commercial release of Crebiliti. This is not a traditional software engineering role. You will be expected to architect systems, decompose complex technical problems and use modern AI engineering tools to dramatically accelerate software development. The ideal candidate is an engineer who enjoys solving difficult architectural problems rather than simply implementing specifications.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Responsibilities
You will help design and implement systems including:
- Enterprise retrieval systems
- Evidence positioning engines
- Multi-model AI orchestration
- Knowledge retrieval pipelines
- Semantic reasoning components
- Enterprise APIs
- Production infrastructure
- Performance optimisation
- Evaluation and regression frameworks You will work directly with the Founder and Chief Architect to transform an advanced research prototype into an enterprise-ready platform.
Essential Skills
Strong experience in several of:
- Python
- FastAPI
- PostgreSQL
- OpenSearch or Elasticsearch
- Vector search
- LLM APIs
- RAG architectures
- Agentic software engineering
- Docker
- Kubernetes
- Git Experience with cloud infrastructure is advantageous.
What We Value Most
We care less about years of experience than about how you think. We're looking for engineers who:
- think architecturally;
- break problems into elegant systems;
- challenge assumptions;
- enjoy learning rapidly;
- use AI as a force multiplier rather than a code generator;
- take ownership of outcomes.


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Working Style
- Small team.
- High autonomy.
- Minimal meetings.
- Rapid iteration.
- Heavy use of AI-assisted engineering.
- Engineering decisions based on evidence rather than hierarchy.
Contract
Initial six-month contract focused on delivery of an enterprise pilot. High-performing team members are expected to transition into permanent leadership roles as the company grows. Remote working initially, with opportunities to relocate to the UAE as the company expands.
Why Join?
- Opportunity to help create a new category of AI assurance technology.
- Work directly with the Founder on technically challenging problems.
- Shape the architecture of a product intended for enterprise and government adoption.
- Help build technology designed to make AI systems transparent, auditable and trustworthy.
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