Applied AI Manager

Qualifications

• The problems you'll work on are specific to this market: extracting logic from legal indentures, building models on top of loan-level tape data, automating waterfall calculations, and turning messy deal documentation into clean, reliable data pipelines

• Have proven experience leading engineering teams in a fast-paced, high-growth environment

• Understand structured finance well enough to build on top of it: loan tapes, cash flow waterfalls, ABS/CLO structures, priority of payments

• You don't need to be a banker, but you need to know what a delinquency trigger is and why it matters

• Have hands-on experience building and deploying ML/GenAI systems in production in finance, legal, or other high-complexity, data-heavy domains

• Can lead architectural discussions and technical trade-offs without losing sight of the details

• Bonus points for experience with NLP and document processing on financial contracts, RAG or LLM-based applications on structured data, large-scale loan data pipelines, or containerization tooling (Docker, Kubernetes, Terraform)

• 4 more items(s)

Benefits

• Competitive salary + performance-based bonus

• Stock option plan

• Hybrid working model with flexible hours

• Regular team events and annual retreats

• Referral bonus program

• Daily perks: snacks, lunch options, good coffee

• 3 more items(s)

Responsibilities

• You'll work on genuinely hard problems: structured finance data is complex, high-stakes, and largely unstructured, and you'll build systems that actually change how the market operates

• 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, 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 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

• Are familiar with cloud infrastructure (AWS preferred) and modern MLOps practices

• Care about people development: mentoring, performance conversations, building teams that do their best work

• 8 more items(s)

More job highlights

Job description

About Cardo AI

Cardo AI is the platform powering private credit and Asset-Based Finance, a $40 trillion market that still runs on fragmented data, manual workflows, and outdated infrastructure.

We're changing that.

Since 2018, we've built the tools that banks, trustees, and investors use to optimize portfolios, streamline transactions, and move faster in complex markets. Over $40Bn in assets run... through our platform, and institutions like Blackstone and Encina trust us to power their private credit strategies.

We've recently closed a funding round co-led by Blackstone and FinTop Capital to accelerate that mission.

We're at an inflection point: proven product-market fit, strong global traction, and a clear path to becoming the category-defining platform for ABF and private credit worldwide.

The Opportunity

The Data Science & AI team is growing, and we're looking for an Applied AI Manager to lead our application of AI across the platform and the business.

You'll work on genuinely hard problems: structured finance data is complex, high-stakes, and largely unstructured, and you'll build systems that actually change how the market operates.

This isn't a research role.

We need someone who ships.

The problems you'll work on are specific to this market: extracting logic from legal indentures, building models on top of loan-level tape data, automating waterfall calculations, and turning messy deal documentation into clean, reliable data pipelines.

Generic ML experience won't cut it here.

You need to understand what the data means.

Here's the kind of work you'll own:

• 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, 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 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

About You

This role is a strong fit if you:

• Have proven experience leading engineering teams in a fast-paced, high-growth environment

• Understand structured finance well enough to build on top of it: loan tapes, cash flow waterfalls, ABS/CLO structures, priority of payments.

You don't need to be a banker, but you need to know what a delinquency trigger is and why it matters

• Combine strong software engineering (Python preferred) with deep knowledge of AI/ML frameworks, GenAI tooling, and modern data infrastructure

• Have hands-on experience building and deploying ML/GenAI systems in production in finance, legal, or other high-complexity, data-heavy domains

• Can lead architectural discussions and technical trade-offs without losing sight of the details

• Are familiar with cloud infrastructure (AWS preferred) and modern MLOps practices

• Care about people development: mentoring, performance conversations, building teams that do their best work

Bonus points for experience with NLP and document processing on financial contracts, RAG or LLM-based applications on structured data, large-scale loan data pipelines, or containerization tooling (Docker, Kubernetes, Terraform).

Why Cardo AI

You'll own meaningful work in a market that's large, underserved, and moving fast.

The problems are real, the data is genuinely complex, and the team is strong.

There's real room to shape how AI gets applied across the business and the industry.

What We Offer

• Competitive salary + performance-based bonus

• Stock option plan

• Hybrid working model with flexible hours

• Regular team events and annual retreats

• Referral bonus program

• Daily perks: snacks, lunch options, good coffee

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