Description
Compensation
The expected base salary range for this role is circa CA$0 – CA$150K. This range is a good-faith estimate of what we expect to pay for this role. Actual pay will vary based on factors such as job-related skills, experience, and internal equity.
What do we do?
Paddle offers digital product companies a completely different approach to their payment infrastructure. Instead of assembling and maintaining a complex stack of payments-related apps and services, we’re a Merchant of Record for our customers. That means we take away 100% of the pain of payment fragmentation. It’s faster, safer, cheaper, and, above all, way better.
We’re backed by investors including KKR, FTV Capital, Kindred, Notion, and 83North and serve over 10,000 software sellers in 245 territories globally.
The role:
We’re looking for an entrepreneurial and technically strong Senior AI Engineer to join our Data & AI team and work with our Go-To-Market organisation.
This is a builder's role, end to end. You’ll work closely with Marketing, Sales, and RevOps to solve high-value problems, design practical AI solutions, and build them into reliable systems that people use every day. You’ll be expected to move comfortably from an ambiguous business challenge to a technical design, a working prototype, and then a production-ready solution.
Your work could include building systems that segment and prioritise accounts, developing agents that automate sales workflows, or creating intelligent tools that help our teams research prospects and act on buying signals. You’ll own the full lifecycle of what you build, including evaluation, observability, reliability, and cost optimisation.
This role is ideal for someone who enjoys being close to users, can write production-quality code, and is excited by the challenge of turning rapidly evolving AI capabilities into valuable commercial outcomes. Experience working with GTM teams is useful, but the ability to understand problems, build effective systems, and measure their impact is more important.
Responsibilities
- Design and build AI-powered systems for account segmentation, enrichment, scoring, prioritisation, and buying-signal detection
- Develop and deploy agentic workflows for use cases such as account research, outbound personalisation, call summarisation, and CRM hygiene
- Write production-quality code and build the integrations, data pipelines, and services required to take solutions from prototype to reliable daily use
- Optimise systems for quality, latency, and cost through evaluation, prompt design, model selection, routing, caching, context management, and token optimisation
- Establish practical patterns for building AI systems at Paddle, including monitoring, guardrails, documentation, and clear measures of business impact
Requirements
- Have strong software engineering experience and can independently take a problem from technical design through to production; Python and SQL experience would be particularly relevant
- Have hands-on experience building applications with large language models, APIs, retrieval systems, agents, or other applied AI technologies
- Understand how to evaluate and operate AI systems in production, including managing hallucination risk, latency, reliability, context limits, and variable model costs
- Are comfortable working with structured and unstructured data, building integrations, and turning information from multiple sources into useful systems
- Have an interest in commercial problems and can understand concepts such as ICP, segmentation, pipeline, buyer intent, and sales workflows; direct GTM experience is beneficial but not essential
- Enjoy working directly with the people who use what you build, are comfortable with ambiguity, and can balance speed, quality, and long-term maintainability
Benefits
We offer a full suite of benefits, including attractive salaries, stock options, unlimited holidays, enhanced parental leave, retirement plans, private healthcare, and well-being initiatives.
We invest in learning and will help you with your personal development via constant exposure to new challenges, an annual learning fund, and regular internal and external training.