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Paddle is a Merchant of Record platform that simplifies payment infrastructure for digital product companies, serving over 6,000 software sellers across 245 territories. The company is backed by KKR, FTV Capital, Kindred, Notion, and 83North.
You will join the Data & AI team as a Senior AI Engineer working closely with Go-To-Market functions (Marketing, Sales, RevOps). This is an end-to-end builder role where you'll move from ambiguous business challenges through technical design, prototyping, and production deployment.
Key responsibilities include:
- Design and build AI-powered systems for account segmentation, enrichment, scoring, prioritization, and buying-signal detection
- Develop and deploy agentic workflows for account research, outbound personalization, call summarization, and CRM hygiene
- Write production-quality code and build integrations, data pipelines, and services to move solutions from prototype to reliable daily use
- Optimize systems for quality, latency, and cost through evaluation, prompt design, model selection, routing, caching, and token optimization
- Establish practical patterns for building AI systems at Paddle, including monitoring, guardrails, documentation, and business impact measurement
- Own the full lifecycle of what you build, including evaluation, observability, reliability, and cost optimization
You'll work directly with GTM teams to understand problems, build effective systems, and measure their impact. The role values someone who enjoys being close to users, can write production-quality code, and is excited by turning rapidly evolving AI capabilities into valuable commercial outcomes.
Paddle offers a digital-first, hybrid work environment with unlimited holidays, 4 months paid family leave regardless of gender, an annual learning fund, and regular training opportunities.
Requirements:
- Strong software engineering experience with ability to independently take problems from technical design through production
- Python and SQL experience (particularly relevant)
- Hands-on experience building applications with large language models, APIs, retrieval systems, agents, or other applied AI technologies
- Understanding of how to evaluate and operate AI systems in production, including managing hallucination risk, latency, reliability, context limits, and variable model costs
- Comfort working with structured and unstructured data, building integrations, and turning information from multiple sources into useful systems
- Interest in commercial problems and understanding of concepts such as ICP, segmentation, pipeline, buyer intent, and sales workflows (direct GTM experience beneficial but not essential)
- Ability to work directly with end users, comfort with ambiguity, and ability to balance speed, quality, and long-term maintainability
