Ki
Algorithm Engineering Manager

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Who are we?đź‘‹
Look at the latest headlines and you will see something Ki insures. Think space shuttles, world tours, wind farms, and even footballers’ legs.
Ki’s mission is simple. Digitally disrupt and revolutionise a 335-year-old market. Working with Google and UCL, Ki has created a platform that uses algorithms, machine learning and large language models to give insurance brokers quotes in seconds, rather than days.
Ki is proudly the biggest global algorithmic insurance carrier. It is the fastest growing syndicate in the Lloyd's of London market, and the first ever to make $100m in profit in 3 years.
Ki’s teams have varied backgrounds and work together in an agile, cross-functional way to build the very best experience for its customers. Ki has big ambitions but needs more excellent minds to challenge the status-quo and help it reach new horizons.
Where you come in?
We're looking for an Algorithm Engineering Manager to join our algorithmic underwriting team. In this role, you'll partner with our Head of Algorithm Engineering to build and guide an effective algorithm engineering team, while helping us shape the bold vision of our underwriting algorithm.
You'll collaborate with colleagues across our business to solve exciting organisational and technical challenges. Together, we'll answer questions like: How can we organise our algorithm engineers for the greatest impact? And how can we share our company's future vision clearly with our team to help them shape the direction of algorithm engineering?
We're a multi-disciplined, commercially-focused team that brings together deep expertise in specialty insurance and scalable algorithm product development. Our squads focus on delivering high-impact features, and we favour a highly iterative, analytical approach. We love discovering new possibilities, so we actively invest time in research and development, both internally and with leading academic institutions.
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 you will be doing: 🖋️
- Act as an advocate for the vision of Ki’s Underwriting Algorithm both within the team and the wider community.
- Keep current with trends and issues in the technology industry. Advise, counsel, and educate executives and management on their competitive or financial impact.
- Help shape and execute Algorithm Engineering team’s strategy.
- Work with the algorithm and engineering leadership to shape the architecture across algo related domains and their interfaces with the rest of the engineering org and seek to reduce complexity and solve problems through it.
- Ensure that Ki is well positioned to explore new algorithmic underwriting strategies, and exploit emerging technologies.
- Help senior leadership to understand algorithm engineering capabilities and use to develop Ki’s product and strategy and guide investment to support this strategy.
- Work with colleagues to create and iterate governance processes around model lifecycle management, advocating and upholding model management best practices.
- Liaise with stakeholders to structure and evolve the roadmap for Ki’s Underwriting Algorithm.
- Managing and building a high-performance Algorithm Engineering team, influencing the hiring and development strategy of the team.
- Drive improvements in the way we operate as a digital underwriting capability.


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Requirements
- Bachelor’s degree or higher in a STEM field, or equivalent practical experience (a PhD in a STEM field is a plus).
- Commercially minded.
- Understanding of the control and management of data products.
- Experience with Python programming and various software design patterns.
- Direct experience with at least one cloud provider.
- Experience interfacing and communicating with stakeholders on the value and execution of algorithmic approaches to commercial problems.
- Managing data science or engineering activity via both people management and technical leadership.
- Experience developing industrialised machine learning applications and services.
- Understanding the importance of market compliance and core regulatory requirements.
- Understanding of what it takes to build a good engineering culture.
Benefits
You’ll get a highly competitive remuneration and benefits package. This is kept under constant review to make sure it stays relevant. We understand the power of saying thank you and take time to acknowledge and reward extraordinary effort by teams or individuals.
What to expect during the recruitment process
- Initial recruiter screening call
- Interview with hiring manager
- Technical Interview (this may vary depending on the role)
- Values Interview
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