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About us At Xelix, we work with some of the world’s largest companies to automate and strengthen their financial controls. Our AI solutions redefine how Accounts Payable teams operate – moving from manual processes to automated, intelligent workflows. Xelix is a fast-paced scale-up – things move fast and expectations are high. We raised our Series B with Insight Partners in June 2025 and are expanding aggressively. We have a team 150 talented people pulling together to achieve our goals. Everyone is trusted to take ownership, move fast and have a meaningful impact. We prioritise personal and professional growth, keep things fun, and love to celebrate a milestone together. In this role you’ll grow, be challenged and help shape the future of Xelix. If you’re excited about building something special with us, we’d love to hear from you. About the role We are hiring an AI Engineer to join our growing AI Engineering team. You’ll design and build production AI systems — combining machine learning, large language models, and strong engineering — to solve real problems across documents, email, and financial data. We focus on building systems that work reliably in production, not just prototypes. We use modern AI tools extensively in our workflow, enabling engineers to operate at a higher level — focusing on system design, product thinking, and solving complex problems. What you'll be doing AI Systems & Agents: design and build production AI systems — including agent-based workflows, tool use, and multi-step reasoning. Model Development & Adaptation: develop and improve models across text, vision, and structured data, including fine-tuning and hybrid ML + LLM approaches. LLM Platform Work: work with hosted and self-hosted models, contributing to decisions around model selection, performance, and cost. Production Engineering: write clean, maintainable Python and contribute to scalable, observable systems. Evaluation & Iteration: design evals, measure performance rigorously, and improve systems using real-world feedback. AI-Assisted Development: use modern AI coding tools to move faster while maintaining high standards. Collaboration: work closely with product and engineering teams to deliver high-impact features. What you’ll bring Experience: 2–5 years building and shipping ML or AI-powered systems into production. Strong Engineering Skills: clean, testable Python; solid software design; experience working in production environments. AI/ML Breadth: experience with either traditional ML (e.g. gradient boosting) and/or LLM systems (prompting, tool use, evals, agents). Systems Thinking: ability to reason about trade-offs (accuracy, latency, cost, reliability) and design accordingly. Data Skills: SQL, pandas, and experience working with messy real-world data. AI-Native Workflow: comfortable using AI-assisted coding tools effectively. Curiosity & Ownership: proactive in exploring new approaches and improving existing systems. Collaboration: strong cross-functional working style.
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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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.
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.
What we offer in return 💰 Competitive salary of £65,000 to £75,000 depending on experience 🏝️ 27 days of annual leave (including 3 days Christmas closing) which increases up to 3 days based on tenure, with the option to roll over, buy or sell up to 3 days 🏡 Hybrid working with two days a week from our dog-friendly Hoxton office 💪 On-site gym and cycle to work scheme 🛍️ Employee discount at over 100 retailers 🏥 Comprehensive private medical & dental cover with Vitality 🍼 Enhanced parental leave pay 📚 Learning & development culture – £1,000 personal annual budget 🌍 We’re carbon-neutral and are working towards ambitious carbon reduction goals 🎯 Lots of team socials & activities ☀️ Annual team retreat


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Want to learn more? About us Xelix blog Xelix news Xelix glassdoor We believe that people from diverse backgrounds, with different identities and experiences make our company and product better. No matter your background, we'd love to hear from you! And if you have a disability, please let us know if there's any way we can make the interview process better for you - we're happy to accommodate! If you're a recruiting agency - we have an existing list of agencies we work with if required and we are not currently planning on expanding the list. Neither the Talent team nor hiring managers or the Support team will respond to cold outreach. This is a full-time position, with standard working hours from 9:00 AM to 6:00 PM, Monday through Friday. Interview Process While the exact process may vary slightly depending on the role, our typical interview stages are: Introductory Call – A short Teams conversation with a Talent Partner to discuss your background and the opportunity. Hiring Manager Interview – A 30–45 minute Teams meeting to explore your experience and fit for the team. Technical Task or Presentation – A role-relevant exercise to demonstrate your skills and approach. Final On-site Interview – An in-person meeting with our senior leadership team and co-founders at our office. We strive to make the process clear, efficient, and respectful of your time.
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