Senior Software Engineer – AI Infrastructure

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Есть о чём спросить

Навык востребован (engineer). Но вилки нет, про деньги придётся договариваться с нуля.

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Наша компания

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 at scale. This 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.

Чем предстоит заниматься

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

Наши требования

5+ 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

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 0→1 or platform-building teams

Unless a specific application deadline 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

We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance

Our commitment

Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto

We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision

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