Staff Software Engineer | AI.

Accountabilities:

As a senior technical contributor, you will lead the development and integration of AI-powered capabilities while ensuring they are reliable, scalable, secure, and aligned with customer and business needs. Your responsibilities will include:

• Collaborate with product managers and business stakeholders to identify challenges and translate them into effective AI-driven solutions.

• Design, develop, and integrate AI features into existing SaaS products, expanding platform capabilities and improving the customer experience.

• Partner with data teams to ensure relevant data is collected, enriched, prepared, and made available for AI applications.

• Build, test, and evaluate AI-powered services, progressing from customer-facing prototypes to production-grade solutions available at scale.

• Write high-quality Python code to manipulate data, interact with large language models, and evaluate the performance and reliability of AI systems.

• Develop tools, services, and infrastructure that support secure, scalable, and dependable AI deployment.

• Collaborate with cloud operations teams to deploy AI features, monitor performance and business impact, and continuously optimize production systems.

• Apply modern AI technologies and engineering practices to improve workflows, support better decision-making, and enable product innovation.

• Contribute technical leadership and engineering best practices across the AI development lifecycle, from experimentation and evaluation through production deployment and ongoing improvement.

Requirements:

The ideal candidate is an experienced software engineer with a strong background in production systems and practical AI implementation. You should be comfortable navigating complex technical challenges, collaborating across disciplines, and turning emerging technologies into dependable customer-facing capabilities. Key qualifications include:

• 10+ years of professional software engineering experience, ideally in full-stack SaaS application development or backend engineering.

• A proven track record of building and deploying production-ready AI or machine learning services at scale.

• Hands-on experience with large language model frameworks, platforms, evaluation methods, and related AI tooling.

• Strong Python development skills or equivalent expertise in a modern programming stack, with familiarity in data manipulation and model evaluation workflows.

• Experience building scalable data infrastructure and integrating AI models into broader SaaS systems.

• Experience with AWS or an equivalent cloud environment, along with modern DevOps practices.

• Demonstrated ability to use AI tools and technologies to improve workflows, enhance decision-making, or drive innovation.

• Strong problem-solving skills and the ability to translate business requirements into maintainable, production-quality technical solutions.

• Effective communication and collaboration skills, with the ability to work closely with engineering, product, data, and cloud operations teams.

Benefits:

• Annual salary range of $150,000–$190,000. Compensation may vary by work location, particularly outside the United States, Austin, and California, as well as by experience, skills, education, and other job-related factors.

• Medical, dental, and vision insurance options, including a company-paid high-deductible health plan for employees.

• Competitive financial benefits, including annual bonuses, equity options, and a 401(k) or RRSP for eligible employees in Canada, with a company match.

• Flexible paid time off and paid holidays.

• Parental leave to support new parents.

• Wellness stipends, mental health support, and one-on-one nutrition coaching.

• Professional development opportunities through internal learning programs, leadership development, and individual development funding.

• Charitable donation matching, paid volunteer time, and company-sponsored volunteer activities.

• Virtual and in-person team-building events, employee recognition programs, and peer-to-peer appreciation initiatives.

• A collaborative and inclusive culture that emphasizes continuous learning, employee well-being, and opportunities to make a meaningful impact.