Senior Software Engineer, Back End & Infrastructure

• 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

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., * 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 production systems
• Strong communication skills and the ability to influence technical direction
• Actively leverage LLMs or AI tooling to improve engineering workflows
• Must be able to work in our Seattle or NYC office 3 days per week (hybrid model), * Experience operating systems across multiple cloud providers
• Has built or supported generative AI, LLM, or ML-powered systems
• Experience designing event-driven systems using queues or streaming infrastructure
• Previous or current experience in startup or high-growth environments
• Proficiency in utilizing agentic coding tools (e.g., Claude Code).

• Curiosity: We start with questions, not assumptions, and follow the signal wherever it leads.
• Velocity: We move fast, iterate quickly and prefer learning through doing.
• Empathy: We’re ambitious, but never at the expense of being respectful, inclusive and grounded.
• Openness: We welcome different perspectives and challenge each other’s ideas
• Ownership: We trust people to own decisions and outcomes.

Compensation Philosophy & Benefits

Our salary ranges are based on paying competitively for our size and industry. Salary is just one part of our total compensation package that includes equity, perks & benefits, and development opportunities at Evertune AI. Individual pay decisions are based on several factors, including qualifications for the role, experience level, skillset, geography, and balancing internal equity relative to other Evertune AI employees. It is our expectation that the majority of candidates who are offered roles at Evertune AI will land well within our salary ranges based on these factors.

The annual base salary range for this position is: $120,000 - $300,000 + stock options.

Benefits include: Competitive Equity, Medical/Dental/Vision Coverage, Generous Paid Time Off, Commuter Benefits, etc.

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.