Software Engineer (Agentic AI Infrastructure)

• 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

Benefits

• Competitive equity
• Company-wide holidays and paid time off
• 100% paid medical, dental, and vision
• Generous parental leave
• Bi-annual company-wide offsites or onsites
• One Medical membership
• Learning and development stipend

• 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
• 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 think carefully about architecture and tradeoffs, and you’re comfortable leading technical decisions without a complete playbook
• You have a strong systems engineering background, with 3+ years of experience building and operating distributed, production-grade systems
• You have experience with the full software development lifecycle: design, code review, testing, deployment, and on-call ownership
• 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’re energized by ambiguity—you can take a fuzzy problem, break it down, and ship something real
• You’ve designed services that are scalable, resilient, and fault-tolerant—and you’ve done it more than once