Software Engineer, Applied AI; Seattle

PLEASE NOTE:
At this time, we are only able to consider candidates who are authorized to work in the United States without the need for current or future visa sponsorship. This includes U.S. citizens and Green Card holders.

Evertune is building the first AI discovery platform for modern marketers. As large language models (LLMs) become the go-to source for recommendations – we help brands understand exactly what AI is saying about them, where they stand against competitors, and how to show up more often in AI-powered answers. Our platform turns black-box AI behavior into actionable insights, so marketing teams can make faster, smarter decisions that drive growth.

Founded by leaders who helped scale The Trade Desk into the world’s leading ad tech platform, we bring deep expertise in digital advertising, data, and high-growth environments. Now, we’re pioneering a new category at the intersection of AI, SEO, and brand strategy.

We recently announced our $15M Series A led by Felicis Ventures, with support from Eniac, Next View, Roger Ehrenberg, and leaders from OpenAI, Google, Meta, Uber, and more. This gives us the momentum to move faster and build the first enterprise-grade AI marketing suite.

Backed by top-tier VC investors and trusted by forward-thinking brands, we have the resources to scale – but what really defines us is our culture. We move fast, think boldly, and believe the best ideas win regardless of title. If you're excited about shaping the future of how brands grow in the age of AI, you’ll thrive here.

You’ll be joining Evertune’s software engineering team – a tight-knit, high-velocity group, with most of us based in Seattle and New York. While we span time zones, we operate with tight alignment and shared urgency. Our engineers optimize for high velocity: we ship fast, sweat the details, and genuinely enjoy building together.

As a foundational hire, you'll be helping to shape not just how we code – but how we grow, communicate, and scale.

In this role, you’ll focus primarily on backend engineering — building the systems that power our AI Discovery platform. You’ll work at the bleeding edge of evaluating and applying LLMs to real-world problems, from designing resilient APIs to optimizing real-time AI integrations. You’ll collaborate across the stack to deliver features quickly and reliably, working side-by-side with other engineers, designers, and product managers.

This is a great role for someone who thrives on solving hard technical problems and wants to grow quickly in a high-ownership environment. You’ll ship meaningful features, learn from experienced teammates, and benefit from a strong mentorship culture that will help you level up fast. You’ll gain exposure to everything from system design to cloud infrastructure. If you’re excited about building in the AI space and want to move fast with a small, talented team, you’ll fit right in.

• Build and maintain backend services in Python
• Design and optimize data pipelines, storage systems, and real-time AI integrations
• Help integrate and test data from third-party APIs, including LLM providers like OpenAI and Anthropic
• Collaborate with other engineers to deliver robust, user-facing features
• Debug and troubleshoot issues across the stack to ensure reliability and performance
• Participate in code reviews, standups, and sprint planning to support a high-velocity release cycle
• Contribute to team best practices, documentation, and internal tooling as we scale

• 3–8 years of professional experience in backend or full stack software engineering, building high-quality user-facing or B2B products
• Strong proficiency with modern backend languages (Python, Go, or similar)
• Experience designing scalable, high-performance data models and APIs
• Comfort working with distributed systems and cloud platforms (preferably GCP)
• Familiarity with integrating third-party APIs, especially high-throughput or real-time systems
• Excellent communication skills and a collaborative mindset
• Must be able to work in our Seattle office 2–3 days per week (hybrid model)

• Experience working with LLM APIs or ML…