Senior Software Engineer – AI Infrastructure

🔥 3 hours ago

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Kraken Digital Asset Exchange

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2011

₿ Crypto

💸 Finance

💳 Fintech

Crypto • Finance • Fintech

Kraken Digital Asset Exchange is a cryptocurrency platform that facilitates the buying and selling of over 200 cryptocurrencies, including Bitcoin, Ethereum, and many others. Founded in 2011, Kraken provides a comprehensive suite of features for both beginner and advanced traders, such as advanced trading interfaces and margin trading. The platform emphasizes industry-leading security, deep liquidity, and 24/7 customer support, making it a trusted choice for users worldwide. Kraken caters to individual investors as well as institutional clients, offering services like OTC trading and custody. The company is committed to transparency with its proof of reserves and mission-driven values. Kraken operates globally, supporting clients in over 190 countries, with a quarterly trading volume exceeding $207 billion. However, users are advised of the high risk of crypto investments and the lack of regulation in some jurisdictions.

📋 Description

• 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

🎯 Requirements

• 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

🏖️ Benefits

• Health insurance • 401(k) matching • Flexible work hours • Paid time off • Remote work options