At a Glance
- Tasks: Build innovative AI systems to empower scientists and accelerate discovery.
- Company: Join a collaborative team at the Ellison Institute, focused on impactful science.
- Benefits: Enjoy enhanced holiday pay, private medical insurance, and an electric car scheme.
- Other info: Be part of a supportive environment that values creativity and teamwork.
- Why this job: Shape the future of AI in science and make a real difference.
- Qualifications: Experience in building AI products and full-stack development.
The predicted salary is between 63000 - 77000 £ per year.
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.
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.
- Nice to Have
- 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.
Benefits
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!
#J-18808-Ljbffr
Software Engineer - Life AI Platform in Oxford employer: Ellison Institute of Technology Oxford
At EIT, we are dedicated to fostering a collaborative and inclusive work environment that empowers our employees to take creative risks and make meaningful contributions. As a Software Engineer on our Live AI Platform, you will have the unique opportunity to work closely with scientists, shaping innovative solutions that drive scientific discovery while enjoying comprehensive benefits and a strong commitment to personal and professional growth.
Contact Details:
Ellison Institute of Technology Oxford Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Software Engineer - Life AI Platform in Oxford
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We think you need these skills to ace Software Engineer - Life AI Platform in Oxford
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Ellison Institute of Technology Oxford.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Ellison Institute of Technology Oxford and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Ellison Institute of Technology Oxford
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Ellison Institute of Technology Oxford uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
