Senior Software Engineer – AI Infrastructure

Building the Future of Open Finance Payward - the parent company behind Kraken, Ninja Trader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system.

Before you apply, we encourage you to explore our culture page to understand what drives us and how we work.

The team Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients.

The AI Infrastructure team builds and operates the production systems that power intelligent agents s team sits at the foundation of the agent platform, ensuring that model inference, orchestration, and execution layers are reliable, observable, and performant under real-world load.

Working closely with the Agent Systems team and broader infrastructure partners, this group owns the core primitives that enable agents to safely operate across internal systems. The environment is high-scale and high-stakes — systems serve millions of users and must meet strict reliability, latency, and correctness standards.

This is a deeply production-oriented team. Engineers here combine strong systems thinking with applied ML infrastructure experience, building in Rust and operating services where performance and failure modes matter.

The opportunity

Design and build the infrastructure layer powering AI agent systems in production

Develop high-performance Rust services that handle model inference, orchestration, and execution

Architect scalable systems capable of supporting millions of users and high request throughput

Build reliable ML infrastructure and MLOps patterns for model deployment, evaluation, and monitoring

Define guardrails, observability, and failure handling for agent-driven workflows

Optimize latency, throughput, and cost across inference and orchestration layers

Partner closely with the Agent Systems team to translate experimental prototypes into hardened production systems

Contribute to foundational infrastructure decisions in a high-scale, high-impact environment

What You Bring5+ years of experience building and operating high-scale production systems

Strong proficiency in Rust and systems-level programming

Deep understanding of distributed systems, reliability engineering, and performance optimization

Experience operating services serving millions of users or high-throughput workloads

Familiarity with ML infrastructure, model serving, or MLOps in production environments

Experience designing observability, monitoring, and failure recovery systems

Strong collaboration skills working across infrastructure and applied engineering teams

High ownership mindset in high-stakes production environment

Nice to haves

Experience building infrastructure for agent-based or LLM-powered systems

Background in high-performance networking, async systems, or low-latency architectures

Experience with container orchestration and cloud-native infrastructure

Familiarity with evaluation frameworks and model performance monitoring at scale

Experience working in fast-moving 01 or platform-building teams

Unless a specific Final date to receive applications is stated in the job posting, applications are accepted on an ongoing basis.

Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution.

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