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Ellison Institute of Technology

Software Engineer - Live AI Platform

Oxford
Posted about 22 hours ago
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Job Summary

Within EIT’s AI and Robotics team, we believe powerful AI and increasingly capable robotics will meaningfully accelerate science discovery.

We are building a platform to empower scientists to move from a question, to a designed experiment, to a result on the bench—without having to do the plumbing themselves. This is an undefined product category. You will be part of the founding team to shape the product and the architecture. To begin with, you'd be building for EIT's own scientists, in the same institute. They're a short walk from your desk, not behind an account manager or a research panel.

You’ll own the system architecture from model endpoint to interface. We build prototypes to learn from, and we're willing to throw them away. What comes next depends on what that pilot teaches us, and you'll have a large hand in deciding it.

This role starts as an individual contributor, with the opportunity to build a team over time. You become the technical anchor for how AI models reach the scientists who need them — the person who owns that seam and establishes the technical approach.

Day-to-Day, You Will

  • Build an agentic workflow for scientists end to end, from model endpoints to the user interface. There is nobody to hand a ticket to at the beginning.
  • Build and operate the technical foundations for agentic systems, including orchestration, tool interfaces, state management, evaluation, observability and failure recovery.
  • Design evaluative frameworks to understand if the deployed model is working.
  • Work directly with scientists, observe how they operate and translate what you learn into clear engineering priorities.
  • Synthesise the knowledge from individual workflows to build generalisable capability.
  • Partner with product, data and research to shape the roadmap and ship at speed in an emerging category where the most impactful problems remain unsolved.

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.

Start with a chat, not a search bar

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

Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.

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 We're Looking For

  • You’ve built and shipped systems from scratch as a core engineer and independent contributor or have created something new and standalone inside a larger organisation. You can turn an open-ended problem into a clear technical strategy and working software.
  • You’ve built agentic AI products, not just used them. You understand orchestration, tool use, human-in-the-loop review and evaluation, and have dealt with agents and their typical failure modes.
  • You’ve designed and built production-ready systems. You can make sound decisions about APIs, data models, testing, deployment, observability and failure recovery.
  • You’ve built policy-aware systems with durable audit trails. Constraints are enforced by design, and every decision leaves a trustworthy, queryable record.
  • You are full-stack and self-sufficient. You can take a system from model endpoint to production interface without waiting for someone else to fill the gaps.
  • You can create clarity from ambiguity. You are comfortable setting technical direction and making trade-offs between what is technically elegant and what users need for adoption.

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Nice to Have

Any of these is a meaningful plus:

  • A strong plus: direct life-science or lab experience – for example in protein design, computational biology, bioinformatics, or building tools alongside bench scientists.
  • Building the internal tooling and standards that let a team work with coding agents well - not just doing it yourself.
  • Scientific visualisation - 3D molecular structure, large result sets, comparison and triage interfaces.
  • Experience as an engineering lead or manager who has chosen to come back to building. We'd want to talk about why.

We offer the following salary and benefits

  • Enhanced holiday pay
  • Pension
  • Life Assurance
  • Income Protection
  • Private Medical Insurance
  • Hospital Cash Plan
  • Therapy Services
  • Perk Box
  • Electric Car Scheme

Why work for EIT

At the Ellison Institute, we believe a collaborative, inclusive team is key to our success. We are building a supportive environment where creative risks are encouraged, and everyone feels heard. Valuing emotional intelligence, empathy, respect, and resilience, we encourage people to be curious and to have a shared commitment to excellence. Join us and make an impact!

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Skills

Software engineering
Agentic AI
System architecture
Orchestration
Tool interfaces
State management
Evaluation frameworks
Observability
Failure recovery
Full-stack development
API design
Data modeling
Policy-aware systems
Computational biology
Bioinformatics
Scientific visualization

Location

Oxford, England, United Kingdom

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