Senior Software Engineer, Growth (AI)

Location: Remote, Poland

Company

Go-to-market SaaS platform providing verified B2B contact data and sales and marketing engagement tools for companies worldwide.

What you will do

• Develop engineering strategies that enable rapid experimentation and data-driven growth decisions.
• Build scalable onboarding flows, personalization engines, viral loops, and other growth initiatives.
• Collaborate with Product, Design, Marketing, Data Science, and Engineering to optimize growth metrics.
• Implement A/B testing, analytics instrumentation, automation, and machine-learning-driven engagement improvements.
• Write documented, maintainable code and deliver responsive, accessible, performant interfaces.
• Maintain technical excellence across code quality, continuous delivery, security, performance, and scalability.

Requirements

• At least 5 years of experience in frontend or full-stack development for large-scale applications.
• Proficiency in JavaScript, TypeScript, React, Redux, HTML, CSS, and at least one backend language: Ruby/RoR, Python, or Node.js.
• Experience with AWS or GCP, REST APIs, analytics tools, and A/B testing platforms.
• Proven experience using AI tools to improve software development productivity, debugging, and code generation.
• Strong UX and product judgment, attention to detail, and understanding of performance, accessibility, and scalability.
• Degree in Computer Science or equivalent experience, plus strong communication, leadership, and stakeholder-management skills.

Nice to have

• Growth experience in a startup or scaling product.
• Knowledge of SEO, CRM tools such as Braze or HubSpot, or marketing automation.
• Familiarity with growth frameworks such as Pirate Metrics and viral loops.

Culture & Benefits

• Permanent employment under an employment contract; this is not a B2B contract.
• Open, collaborative environment with hands-on mentorship and opportunities for career growth.
• Global, cross-functional collaboration with an emphasis on ownership, experimentation, and continuous improvement.
• Autonomy and resources to own the role and deliver measurable impact.
• AI-native culture focused on using AI and automation to improve productivity.