Senior Software Engineer, Back End & Infrastructure (NYC OR 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.

About Evertune AI:

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 raised a $15M Series A led by Felicis Ventures, with support from Eniac, NextView, 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.

Your Team:

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.

Your Role:

You’ll take and share deep technical ownership of the backend systems that power our AI Discovery platform, working at the bleeding edge of evaluating and applying LLMs to real-world problems. This includes designing distributed systems, shaping our cloud and infrastructure patterns, optimizing AI integrations, and making architectural decisions that help us scale quickly and reliably.

You are a software engineer first – someone who understands how to build software systems with strong engineering discipline – but you’re also excited to operate at the infrastructure layer. You understand how a strong and stable infrastructure benefits the entire organization. You can reason about cloud environments, permissions, deployment systems, and performance bottlenecks, and you know how to simplify high-ambiguity systems into clean, reliable abstractions.

Responsibilities

• Architect, build, and maintain scalable backend services in Python and Go
• Design resilient APIs, optimize data pipelines, and improve system performance and reliability
• Own and evolve parts of our cloud infrastructure, including environment configuration and access patterns
• Implement and manage infrastructure as code (Terraform or equivalent)
• Design and maintain containerized services using Docker and modern deployment workflows
• Integrate and test data from third-party APIs, including LLM providers like OpenAI and Anthropic
• Manage performance, cost, and observability across AI integrations and backend systems
• Debug and troubleshoot issues across application and infrastructure layers
• Simplify and scale complex systems to support product growth and increasing data volume
• Influence long-term technical direction and backend architecture
• Mentor junior engineers through code reviews and coaching
• Collaborate across the stack to ship product features quickly and reliably

Requirements

• 7+ years building and owning resilient, high-performance backend systems for user-facing or B2B products
• Strong software engineering discipline - you design testable systems, write meaningful automated tests, and protect against regressions as systems evolve
• Deep proficiency in Python (or similar) and a track record of designing distributed systems
• Operated production workloads in cloud environments (GCP, AWS, Azure, or similar), including IAM, service accounts, access controls, and environment isolation
• Improved the performance and reliability of ambiguous or legacy systems by simplifying architecture and reducing operational risk
• Built and maintained infrastructure as code using Terraform or equivalent
• Designed and deployed containerized services using Docker and modern CI/CD workflows
• Designed scalable data models and worked deeply with databases such as MongoDB or similar
• Integrated and operated third-party APIs at scale with attention to performance, cost, and failure handling
• Worked with observability tooling to monitor, debug, and improve producti