Applied AI Manager Engineering/ Product/ Tech · London · Full-time

Applied AI Manager Engineering/ Product/ Tech · London · Full-time

Full-Time 80000 - 100000 £ / year (est.) No working from home possible
PLP Group

At a Glance

  • Tasks: Lead the design and delivery of AI systems that transform finance.
  • Company: Join Cardo AI, a fintech innovator on a mission to revolutionise asset-based finance.
  • Benefits: Competitive salary, performance bonuses, stock options, and team retreats.
  • Other info: Collaborative culture with opportunities for career growth and mentorship.
  • Why this job: Make a real impact in a fast-paced environment with cutting-edge technology.
  • Qualifications: Experience in leading engineering teams and strong software engineering skills.

The predicted salary is between 80000 - 100000 £ per year.

About Cardo AI

At Cardo AI, we have been on a mission since 2018 to make Private Credit and Asset-Based Finance (ABF) markets more accessible and efficient. Today, with over $40 billion in assets under technology, our platform empowers banks, trustees, and investors to accelerate growth through smarter strategies, faster transactions, and optimized investment portfolios. Driven by a bold vision to help grow the ABF market beyond $40 trillion, we are building a future defined by speed, confidence, and innovation. By combining automated workflows, comprehensive data, and AI-driven insights, we transform complexity into opportunity, enabling our clients to unlock growth and stay ahead.

The Data Science & AI team is growing, and we are looking for an Applied AI Manager to lead our application of AI across the platform and the business. You will work on genuinely hard problems: structured finance data is complex, high-stakes, and largely unstructured, and you will build systems that actually change how the market operates. This is not a research role — we need someone who ships.

What You Will Do

  • Lead the design and delivery of complex ML and GenAI systems — robust, scalable, and built for production.
  • Guide the team across the full AI lifecycle, from experimentation and evaluation through deployment and monitoring, with a strong focus on reproducibility and reliability.
  • Drive architectural decisions for data-intensive, AI-driven applications, making sharp trade-offs between cutting-edge approaches and production readiness.
  • Apply NLP and GenAI to extract structure from unstructured financial documents: credit agreements, indentures, and servicer reports.
  • Build and deploy models that operate on structured finance data, where a logic error has real financial consequences.
  • Mentor and grow engineers across levels, building a high-performing team with a strong engineering culture.
  • Collaborate cross-functionally with Product, Data, and Business teams to shape roadmaps and deliver real impact.
  • Champion AI adoption across the organization and influence company-wide technology strategy.

What You Bring

  • Proven experience leading engineering teams in a fast-paced, high-growth environment.
  • Solid understanding of structured finance: loan tapes, cash flow waterfalls, ABS/CLO structures, and priority of payments.
  • Strong software engineering skills (Python preferred) combined with deep knowledge of AI/ML frameworks, GenAI tooling, and modern data infrastructure.
  • Hands-on experience building and deploying ML/GenAI systems in production within finance, legal, or other high-complexity, data-heavy domains.
  • Ability to lead architectural discussions and technical trade-offs without losing sight of the details.
  • Familiarity with cloud infrastructure (AWS preferred) and modern MLOps practices.
  • Commitment to people development: mentoring, performance conversations, and building high-performing teams.
  • Bonus: experience with NLP on financial contracts, RAG or LLM-based applications on structured data, large-scale loan data pipelines, or containerization tooling (Docker, Kubernetes, Terraform).

Competitive salary and performance-based bonus. Stock option plan. Regular team events and annual retreats. Opportunities for career growth within a fast-scaling fintech innovator. A collaborative, innovative, and entrepreneurial culture that values creativity, initiative, and impact.

Applied AI Manager Engineering/ Product/ Tech · London · Full-time employer: PLP Group

At Cardo AI, we pride ourselves on being an exceptional employer, offering a dynamic and innovative work environment in the heart of London. Our commitment to employee growth is evident through mentorship opportunities and a culture that encourages creativity and initiative, while our competitive salary packages and stock options ensure that your contributions are recognised and rewarded. Join us to be part of a collaborative team that is transforming the Private Credit and Asset-Based Finance markets with cutting-edge AI technology.

PLP Group

Contact Details:

PLP Group Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Applied AI Manager Engineering/ Product/ Tech · London · Full-time

Tip Number 1

Network like a pro! Get out there and connect with people in the industry. Attend meetups, webinars, or even just grab a coffee with someone who works at Cardo AI. You never know who might have the inside scoop on job openings!

Tip Number 2

Show off your skills! If you’ve got a portfolio or any projects that highlight your experience with AI and ML, make sure to share them during interviews. It’s all about proving you can ship and deliver results.

Tip Number 3

Prepare for those tricky questions! Brush up on your knowledge of structured finance and be ready to discuss how you’d tackle real-world problems. They want to see your thought process, so think out loud!

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the team at Cardo AI.

We think you need these skills to ace Applied AI Manager Engineering/ Product/ Tech · London · Full-time

Machine Learning (ML)
Generative AI (GenAI)
Natural Language Processing (NLP)
Software Engineering (Python preferred)
Data Infrastructure
Architectural Decision-Making
MLOps Practices

Some tips for your application 🫡

Tailor Your CV:Make sure your CV is tailored to the Applied AI Manager role. Highlight your experience with ML and GenAI systems, and don’t forget to mention any relevant projects that showcase your skills in structured finance.

Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about AI in finance and how your background makes you the perfect fit for our team. Keep it concise but impactful!

Showcase Your Technical Skills:We want to see your technical prowess! Be sure to include specific examples of your software engineering skills, especially in Python, and any hands-on experience with AI/ML frameworks that you've worked with.

Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity at Cardo AI.

How to prepare for a job interview at PLP Group

Know Your AI Stuff

Make sure you brush up on your knowledge of AI and ML frameworks, especially those relevant to finance. Be ready to discuss your hands-on experience with building and deploying systems in production, as this role is all about practical application.

Understand Structured Finance

Familiarise yourself with structured finance concepts like loan tapes and cash flow waterfalls. Being able to speak confidently about these topics will show that you understand the complexities of the data you'll be working with.

Showcase Your Leadership Skills

Prepare examples of how you've led engineering teams in fast-paced environments. Highlight your mentoring experiences and how you've built high-performing teams, as this role requires strong people development skills.

Be Ready for Technical Discussions

Expect to dive deep into architectural decisions and technical trade-offs during the interview. Brush up on cloud infrastructure and MLOps practices, and be prepared to discuss how you balance cutting-edge approaches with production readiness.