Software Engineer - Life AI Platform
At a glance
Mid-level ML Platform & Ops role at Ellison Institute of Technology. Oxford · full-time.
Pay not stated ML Platform & Ops salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build a scientist-facing agent workflow that connects model endpoints to a usable interface
- Set up orchestration, tool access, state handling, evaluation, monitoring and recovery for agentic systems
- Assess whether deployed models are working, then use findings to guide improvements
- Watch scientists work and turn their needs into engineering priorities and reusable capabilities
- Shape the technical roadmap with product, data and research, shipping prototypes and learning from pilots
What you bring
- You have built and launched a system from the ground up as a core engineer or created a standalone product inside an organization
- You have delivered agentic AI products and understand orchestration, tool use, human review, evaluation and common failure patterns
- You can design production systems across APIs, data models, testing, deployment, monitoring and recovery
- You build policy controls into systems and maintain durable, searchable records of decisions
- You can take work from model endpoint through to production interface without relying on others to fill technical gaps
Who this fits
This role suits a self-directed, full-stack engineer who can turn an open-ended problem into technical direction and working software. You will begin as an individual contributor, with the possibility of building a team later. The role is based onsite in Oxford, and you will work directly with scientists.
From the employer
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.
Requirements
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
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.
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
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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!