AI Analytics Engineer

We are a leading financial platform, building the future of payments, shopping, and banking—a world where consumers and merchants can transact effortlessly, grow together and where we create abundance and generate pride in them. Today, we serve over 2 million customers and partner with more than 20,000 merchants, making Addi Colombia’s fastest-growing marketplace.

We provide banking solutions (deposits, payments, unsecured credit) and commerce services (e-commerce, marketing) using state-of-the-art technology, bridging the financial gap for millions and redefining how people experience financial freedom. As the country’s leading Buy Now, Pay Later provider, we have secured regulatory approval to operate as a bank, unlocking even greater opportunities for our customers. In the past year, we have also achieved profitability, reinforcing the strength of our business model and our ability to scale sustainably.

Our mission has earned the trust of world-class investors, including Andreessen Horowitz, Architect Capital, GIC, Goldman Sachs, Greycroft, Monashees, Notable Capital, Quona Capital, Union Square Ventures, Victory Park Capital, and more, who back our vision for the future. With their support, we are not just growing—we are transforming Latin America’s financial ecosystem and shaping the next generation to shop, pay, and bank in Colombia.

But what truly sets us apart is how we build. We are a conscious company, driven by deep experience in scaling technology, services and products, and we live by our values every day.

This is where you come in. Below, you’ll find what this role is all about—the impact you’ll drive, the challenges you’ll tackle, and what it takes to thrive at Addi. If you’re ready to be part of something big, keep reading.

Own the end-to-end delivery of AI agents for the embedded function from problem identification through production adoption ensuring each shipped agent delivers measurable business impact and raises the team's execution standard for what AI can do.

• Ship AI Agents to Production: Identify high-friction workflows within the embedded team and iterate through testing to reach a stable deployment with active adopters and documented, quantified impact like time saved, cost reduced, or revenue generated.

• Build a Self-Serve Operations Model: Create end-to-end documentation for each shipped agent covering inputs, outputs, failure modes, and resolution steps shortly after launch, enabling any teammate to run or maintain it independently.

• Produce a Prioritized Opportunity Backlog: Conduct structured discovery sessions with key stakeholders in the embedded team to score problems by friction level, feasibility, and estimated impact, delivered as a living document reviewed regularly with the Champion.

• Continuous Improvement: Continuously monitor the performance of shipped agents, identify opportunities for enhancement based on real-world usage and observed failure modes, implement documented improvements shortly after launch, and validate measurable gains in reliability, adoption, or output quality.

   

• Proven experience in SQL and data modeling — accelerated with AI

  • Experience designing data models that AI agents can understand, maintain, and extend.

  • Strong SQL skills for querying and transforming large datasets, using AI to accelerate development, validate logic, and document transformations.

  • Experience applying AI-assisted testing and data quality validation as part of the standard development workflow.

• Demonstrated experience with Python for building AI-powered data workflows

  • Experience building Python applications and automations that connect AI agents with data systems.

  • Track record of delivering Python-based pipelines or AI agents that can run reliably in production.

• Track record of building data pipelines spec-first, with AI as the primary execution layer

  • Experience defining clear specifications for inputs, outputs, transformations, and quality checks before implementation.

  • Comfortable using tools such as Claude Code, LiteLLM, or similar AI development tools as part of the daily engineering workflow.

  • Ability to demonstrate how AI has significantly accelerated the delivery of production-ready data pipelines.

• Experienced with ELT/ETL tools and AI orchestration

  • Hands-on experience with dbt, Airflow, or equivalent orchestration frameworks.

  • Experience integrating AI capabilities into production pipelines, such as intelligent transformations, anomaly detection, or workflow automation.

  • Ability to own data pipelines end to end, including the AI orchestration layer.

• Proven experience with data warehouses and AI-native querying

  • Strong experience working with BigQuery, Snowflake, Redshift, or Databricks at production scale.

  • Experience using AI to optimize queries, improve documentation, and automate monitoring.

• Demonstrated ability to translate business problems into AI-powered data solutions

  • Ability to identify the right solution for a business problem, whether that is a pipeline, an AI agent, a model, or a combination of them.

  • Experience building systems that automate recurring analytical work instead of relying on manual reporting.

• Track record of documentation and stewardship designed for AI replication

  • Experience producing documentation that enables both engineers and AI agents to maintain and extend data systems.

  • Experience shipping data products with AI-assisted monitoring and operational visibility built in.

• Demonstrated ability to ship fast and iterate in ambiguous environments

  • Proven ability to deliver production-ready data solutions quickly using AI-first engineering practices.

  • Comfortable working autonomously, prioritizing effectively, and delivering high-quality solutions with minimal oversight.

• Work on a problem that truly matters – We are redefining how people shop, pay, and bank in Colombia, breaking down financial barriers and empowering millions. Your work will directly impact customers' lives by creating more accessible, seamless, and fair financial services.

• Be part of something big from the ground up – This is your chance to help shape a company, influencing everything from our technology and strategy to our culture and values. You won’t just be an employee—you’ll be an owner

• Unparalleled growth opportunity – The market we’re tackling is massive, and we’re growing faster than almost any fintech lender at our stage. If you’re looking for a high-impact role in a company that’s scaling fast, this is it.

• Join a world-class team – Work alongside top-tier talent from around the world, in an environment where excellence, ownership, and collaboration are at the core of everything we do. We care deeply about what we build and how we build it—and we want you to be a part of it.

• Competitive compensation & meaningful ownership – We believe in rewarding our talent. You’ll receive a generous salary, equity in the company, and benefits that go beyond the basics to support your growth.

   

We believe in a fast, transparent, and engaging hiring experience that allows both you and us to determine if there's a great fit. Here’s what our process looks like:

• Step 1: People Interview (30 min)
  A conversation with a recruiter to get to know you, your experience, and what you're looking for. We’ll also share more about Addi, our culture, and the role.

• Step 2: AI System Design Interview (60 min)
  A dedicated deep dive into your AI systems thinking, where we explore how you approach workflow design, tool selection, and failure handling. We want to see how you design solutions that are not only effective, but also simple for others to run and maintain.

• Step 3: Take-Home AI Exercise
  A hands-on exercise focused on building a simple, working AI prototype for a sample workflow. This gives us a clear look at your prototyping skills, code quality, and how effectively you translate business needs into practical AI tools.

• Step 4: On-site Interview (60 min)
  A deep dive into your Take-Home AI Exercise to review your approach and talk through your implementation. This is designed to give us a clear picture of how you operate day-to-day and how you collaborate with the team.

• Step 5: Stakeholder Interview (30 min)
  A strategic discussion focused on your overall fit and ownership mindset. We want to hear your candid perspective on real AI capabilities versus industry hype, how you navigate failed adoption, and how you approach your own professional growth.

• Step 6: Co-Founder Interview (30 min)
  In this final stage, you’ll meet a member of our leadership team to talk about Addi’s values, culture, and mission. It’s an opportunity to ensure that our goals and vision align, and that this role feels like the right next step for you.

We value efficiency and respect for your time, so we aim to complete the process as quickly as possible. Our goal is to make this experience insightful and exciting for you, just as much as it is for us. Regardless of the outcome, we are committed to always providing feedback, ensuring that you walk away with valuable insights from your experience with us.