Backend Engineer | Seattle meaningful equity

Harrison Clarke are partnered with a fast-growing, early-stage AI company building the financial and operational infrastructure for the next generation of enterprise AI.

As enterprises move from experimenting with GenAI to deploying agents and AI-powered applications at scale, they are facing a fundamental problem:
how do you understand what AI actually costs, what value it creates, and which initiatives are worth scaling?

This company is building the platform that answers that question.

As a Backend Engineer, you’ll play a key role in building the systems that power an enterprise-grade AI economics platform.

You’ll work on backend services that ingest, process, analyze, and expose high-volume data generated by AI applications and agentic workflows. You’ll tackle problems around distributed systems, data processing, APIs, observability, reliability, and scalability while working closely with the founding team.

This is an opportunity to join a small, highly technical team where your work will have significant product and architectural impact.

• Design and build scalable backend services powering the core platform
• Build APIs and services that process and expose AI usage, cost, performance, and business-impact data
• Develop systems capable of handling high-volume, real-time telemetry from GenAI applications
• Work with data pipelines and distributed systems to transform raw AI activity into actionable insights
• Build integrations across AI models, cloud providers, agent frameworks, and enterprise technology platforms
• Contribute to the architecture and technical direction of the backend platform
• Design for reliability, scalability, performance, and observability from the outset
• Work closely with product and engineering to turn ambiguous problems into simple, scalable solutions
• Own projects end-to-end, from technical design through implementation, deployment, and iteration
• Help establish engineering best practices as the team and product scale

• 3+ years of professional software engineering experience
• Strong proficiency in Python, Go, Java, or another modern backend language
• Strong understanding of distributed systems, APIs, databases, and system design
• Experience building systems that process high volumes of data or events
• Experience with cloud infrastructure and modern deployment practices
• Strong understanding of reliability, observability, and performance considerations
• Comfortable operating in an early-stage environment with significant autonomy
• Ability to take ownership of ambiguous technical problems and drive them through to production
• Strong communication skills and a pragmatic, product-oriented approach to engineering