Kiwi

Product Manager

• Lead product initiatives at Kiwi from initial discovery through launch and measurement
• Identify problems and opportunities, set priorities, and take ownership of outcomes
• Investigate customer needs and business problems using data, research, feedback, and team conversations
• Define problems, desired outcomes, and success measures before solution development
• Evaluate options and trade-offs across customer impact, business value, risk, operational needs, and implementation effort
• Work with Design and Engineering to shape solutions and guide development and launch
• Align Risk, Compliance, Operations, and Data on initiative decisions
• Measure post-launch results and improve the product based on learnings

Product Analyst

• Investigate customer journeys and internal processes to understand problems and inform product decisions.
• Translate agreed product decisions into clear requirements, flows, acceptance criteria, and edge cases.
• Identify open questions, inconsistencies, and decisions needed before and during implementation.
• Work with Engineering, Design, QA, Risk, and Operations to resolve questions and ensure everyone understands what will be built.
• Follow up on dependencies, testing, and releases, keeping progress and outstanding items visible.
• Analyze data and feedback to help evaluate the results of product changes.
• Maintain accurate product documentation and propose improvements when you find recurring manual work or problems in existing processes.
• Contribute to the development and continuous improvement of Kiwi's products.
• Support initiatives from detailed definition through launch and analysis of results.

Full-stack Engineer

• Lead the Credit Risk Engineering team, setting technical direction, planning delivery, mentoring engineers, reviewing code, and contributing hands-on to critical work
• Design, build, and operate backend services and APIs integrating risk capabilities into Kiwi's lending products
• Improve reliability of credit decision flows across services and external dependencies, including API contracts, latency, timeouts, failure handling, observability, and incident response
• Partner with Credit Risk and Data Science to integrate models into production and improve MLOps practices, including deployment automation, versioning, testing, monitoring, and rollback
• Improve architecture and maintainability of risk services and integrations while addressing technical debt and delivering new risk capabilities

Engineering Lead, Credit Risk

Data Engineer

• Own the inventory of every credit data source, including TransUnion, Clarity, Plaid, Prism, and internal data from the app and loan servicing
• Define required data, grain, freshness, and destination for each source
• Write data contracts with engineers building vendor integrations
• Confirm raw vendor responses are stored completely for model development and audits
• Monitor freshness, volume, fill rate, and schema for every source and model input
• Set up alerts for feature fill-rate drops, missing vendor fields, and volume deviations
• Track input drift for production models alongside data scientists
• Triage data incidents, identify root causes, route fixes, and track closure
• Own the Credit Risk layer of the Snowflake warehouse, including raw, staging, mart, and feature tables
• Build and maintain pipelines and transformations for application, loan, performance, and vendor data
• Keep modeling datasets reproducible and prevent training-data leakage
• Maintain tables behind Credit Risk dashboards and governed metrics
• Write automated tests for keys, duplicates, ranges, referential integrity, and source reconciliation
• Maintain documentation, lineage, and owner registries
• Support vendor oversight by checking SLAs and reconciling pull counts against vendor invoices

Credit Risk Data Engineer

AI Engineer

• Design, build, and evolve scalable backend services and APIs using Node.js, TypeScript, and Express.js
• Own technical solutions end-to-end from design and implementation through deployment, observability, and production support
• Contribute to backend architecture and architectural and technical design decisions
• Identify, prioritize, and address technical debt
• Apply software design principles and patterns based on context and trade-offs
• Design application boundaries and separation of concerns across services, business logic, and persistence layers
• Design and optimize PostgreSQL schemas, queries, indexes, migrations, and transactional workflows
• Build reliable financial workflows covering idempotency, concurrency, consistency, retries, failure handling, and reconciliation
• Design and maintain REST APIs and integrations with internal systems and external providers
• Design asynchronous and event-driven workflows
• Build reliable, scalable, resilient, secure, and performant systems
• Work with AWS infrastructure and cloud services in production systems
• Improve production visibility through logging, metrics, tracing, monitoring, and alerting
• Investigate production incidents, perform root-cause analysis, and implement sustainable solutions
• Maintain engineering quality through automated testing, code reviews, documentation, and continuous refactoring
• Use AI-assisted engineering tools for development, testing, debugging, code review, and productivity
• Challenge technical decisions and improve engineering standards
• Share knowledge and strengthen the engineering team’s technical capabilities
• Collaborate with Product, QA, Data, Platform, and engineering teams to translate business requirements into technical solutions

Product Manager

Product Analyst

Engineering Lead, Credit Risk

Credit Risk Data Engineer

Backend Developer, AI