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Head of Software Engineering [Riyadh]

London
Posted 4 days ago
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This role requires relocation to Riyadh, KSA

We’re partnering with a fast-scaling deep tech startup building next-generation AI infrastructure that combines cutting-edge hardware and software to deliver high-performance AI compute solutions.

The Opportunity

We’re hiring a Head of Engineering to lead the development of a platform that can operate independently of underlying hardware. This is a critical leadership role focused on building a developer-first system that enables flexibility, performance, and global adoption.

The Role

  • Lead the development of a standalone orchestration platform
  • Define and execute the strategy to decouple software from hardware environments
  • Build and scale a developer-focused platform and ecosystem
  • Drive integrations with OEMs, cloud providers, and infrastructure partners
  • Own platform adoption and commercialisation through partnerships
  • Stay hands-on where needed—maintaining technical credibility with engineering teams
  • Engage with customers and partners at both technical and executive levels

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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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.

P

Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your 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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It searches the market for you

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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.

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Strong

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.

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Strong

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.

What They’re Looking For

  • Minimum 10+ years in software engineering with at least 4 years leading teams of 5 or more engineers.
  • Deep expertise in at least two of: AI infrastructure, MLOps, distributed systems, GPU-accelerated workloads, HPC, or runtime systems programming
  • Strong background in GPU scheduling, KV-cache management, or LLM serving optimisation
  • Hands-on experience deploying and optimising AI infrastructure at production scale, ideally with multiple inference engines, utilities, and training frameworks.
  • Proven ability to ship production software through a full release cycle, not just a prototype
  • Strong fluency in Python, C++, and a systems language (Rust, Go, or modern C); comfort with JavaScript or TypeScript for tooling
  • Solid grounding in Linux internals, containers, GPU drivers, CUDA, and observability tooling

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Nice to Have

  • Direct experience with sovereign AI, on-premise LLM deployment, air-gapped systems, or AI in regulated industries (defence, energy, government, finance, healthcare)
  • Open-source contributions in the AI infrastructure space
  • Prior experience as a founding engineer or senior engineer at a deep-tech startup that reached commercial GA
  • Experience with security primitives: hardware fingerprinting, license enforcement, software protection, code obfuscation
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Skills

Software Engineering
AI Infrastructure
MLOps
Distributed Systems
GPU-accelerated Workloads
HPC
Runtime Systems Programming
GPU Scheduling
KV-cache Management
LLM Serving Optimisation
Python
C++
Rust
Go
Linux Internals
CUDA

Location

London, England, United Kingdom

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