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Palona AI

AI Software Engineer, Growth

Posted 6 Days Ago
In-Office
Toronto, ON, CAN
Mid level
In-Office
Toronto, ON, CAN
Mid level
Build and optimize conversion-focused web experiences, landing pages, demos, and growth systems. Instrument analytics, attribution, and experimentation; integrate APIs and automate workflows; apply AI to content, personalization, and experiment generation; and partner with Growth, Marketing, and Sales to drive qualified pipeline and measurable revenue outcomes.
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Palona is building a category-defining AI platform for restaurants. This role builds the technical growth system that helps the right restaurant owners, operators, franchise leaders, and technology buyers discover Palona, understand its value, experience the product, and become qualified opportunities.

We are looking for an AI Full-Stack Engineer who treats growth as an engineering and product discipline. You will own web experiences, experimentation, SEO and generative-engine optimization, paid acquisition infrastructure, attribution, analytics, and AI-enabled growth workflows. You will work across the public website, landing pages, demos, calculators, content systems, marketing and sales integrations, and the data pipelines that connect acquisition to revenue.

The objective is not broad traffic or dashboard activity. It is a measurable, compounding system for qualified demand and pipeline. You will partner closely with Growth, Marketing, Sales, Product, and Design while remaining a production engineer with a high bar for code quality, performance, measurement, and user experience.

What you’ll own
  • Build fast, compelling, conversion-focused web experiences for high-intent restaurant buyers.
  • Create and iterate on landing pages, interactive demos, ROI tools, comparison experiences, and other acquisition products.
  • Establish reliable end-to-end attribution from source and campaign through demo booking, qualification, opportunity, and closed revenue.
  • Instrument product and marketing events, persist campaign context across domains and tools, and improve data quality across the funnel.
  • Design an experimentation system for messaging, offers, page structure, onboarding, calls to action, and acquisition channels.
  • Improve technical SEO and GEO foundations, including performance, crawlability, metadata, structured data, internal linking, and content architecture.
  • Integrate and automate workflows across analytics, CRM, scheduling, advertising, content, and sales systems using APIs and server-side events.
  • Apply AI to accelerate research, content operations, personalization, campaign analysis, and experiment generation while building appropriate review and quality controls.
  • Analyze funnel behavior and unit economics, identify the highest-leverage bottlenecks, and ship improvements rather than stopping at recommendations.
  • Partner with Growth and Sales to define qualified-conversion metrics and ensure optimization targets reflect pipeline quality, not vanity volume.
  • Build reusable systems so the company can launch new product pages, vertical campaigns, and experiments quickly and safely.

Requirements
  • 3+ years of industrial experience in relevant technical domain.
  • Strong full-stack web engineering experience, ideally with TypeScript, React, Next.js, APIs, and modern deployment platforms.
  • Experience building measurable user funnels, experimentation systems, analytics instrumentation, or growth products in production.
  • Working knowledge of SEO, web performance, conversion optimization, paid acquisition mechanics, and attribution; deep expertise in every channel is not required.
  • Ability to work with data using SQL or analytics tools and translate findings into prioritized product and engineering work.
  • Experience integrating third-party APIs and managing the reliability, consent, identity, and data-quality challenges they create.
  • Strong product taste and the ability to write or collaborate on clear, outcome-oriented customer experiences.
  • A rigorous approach to experimental design and causality; you know the difference between correlation, directional evidence, and a trustworthy test.
  • AI-native working habits and a practical view of where automation needs human judgment.
  • Comfort owning business outcomes and collaborating closely with non-engineering partners.

Benefits
  • Competitive Salary and Stock Option Plan.
  • Medical, dental, vision, retirement, leave, and disability benefits as applicable.
  • Family Leave
  • Short Term & Long Term Disability
  • Paid time off and company holidays.
  • Learning and development support.

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