Software Engineer, Agentic AI Infrastructure

Anrok is the leading tax automation platform enabling businesses to expand globally without compliance complexity.

As the digital economy has grown 6x over the last decade, software businesses have gone from not worrying about sales tax to needing to monitor exposure, calculate rates, and file returns across 50 US jurisdictions and 100+ countries. This creates a critical bottleneck for companies that should be able to transact with customers everywhere.

Anrok eliminates this complexity by connecting with billing and payment systems to automate tax monitoring, calculations, and filing end-to-end. Our unified platform handles the ever-changing maze of tax laws at municipal, state, and federal levels—so companies can focus on growth, not compliance.

Our customers include:

• 40% of Forbes Top 50 AI companies

• 20% of Forbes Top 100 Cloud companies

• Top companies like Notion, Anthropic, and Cursor

We're making compliant digital commerce a reality for companies big and small, backed by over $100M from leading investors including Sequoia, Spark, Index, and Khosla Ventures.

We're building the agentic infrastructure layer at Anrok—the systems that let AI agents reason about tax data, take action across jurisdictions, and operate reliably at scale. This is early and foundational work: you'll be designing and shipping the primitives that the rest of the product builds on. We're looking for an engineer who pairs a strong distributed-systems background with real, hands-on experience building AI agent systems—someone who understands both how to make a service fault-tolerant and what it takes to make an LLM-powered agent reliable in production. If you want to work on distributed systems that sit at the intersection of AI and fintech, this role is for you.

• Design and build the distributed, fault-tolerant infrastructure that powers Anrok's AI agent capabilities—covering memory, state management, and execution for autonomous systems.

• Own technical architecture decisions for new agent infrastructure services end-to-end, from initial design through production deployment and iteration.

• Build the evaluation, observability, and reliability tooling that lets the rest of the team ship agents confidently on top of your infrastructure.

• Collaborate closely with product engineers and our tax data team to translate real compliance workflows into reliable, scalable agent primitives.

• Drive engineering best practices across the team: code quality, testing discipline, system design, and operational health.

• Identify and fix performance, reliability, and scalability bottlenecks as our agent systems grow.

• Help grow the team—mentoring engineers, contributing to technical culture, and raising the bar on how we build.

• You have a strong systems engineering background, with 3+ years of experience building and operating distributed, production-grade systems.

• You've designed services that are scalable, resilient, and fault-tolerant—and you've done it more than once.

• You've built and deployed AI agents or LLM-powered systems in production, and you understand firsthand what makes them reliable and maintainable at scale.

• You're familiar with the modern AI stack—prompt engineering, eval frameworks, RAG pipelines, tool calling, and agent orchestration—and you have a point of view on what the infrastructure beneath it should look like.

• You think carefully about architecture and tradeoffs, and you're comfortable leading technical decisions without a complete playbook.

• You have experience with the full software development lifecycle: design, code review, testing, deployment, and on-call ownership.

• You're energized by ambiguity—you can take a fuzzy problem, break it down, and ship something real.

• You're curious and motivated to learn new tools—you've experimented with AI in your work or on your own, you're excited about what's possible, and you've built something with it (an application, a workflow, a creative solution to a real problem) that you can walk us through.