Kraken
Fintech: Finance + Technology
See how your profile stacks up against this role.
We compared the job requirements to your profile to show where you're strong and where you fall short.
Payward - the parent company behind Kraken, NinjaTrader, 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.
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 sits within the Data organization and is responsible for building, operating, and scaling the systems that power AI agents in production — both internal tools and external-facing products. Working closely with the AI and Agent Systems teams, this group ensures that the orchestration, execution, and model-serving layers underpinning agentic workflows are reliable, observable, and built to scale.
This team operates at the intersection of data infrastructure and applied AI — a space that moves fast and demands engineers who can bring production discipline to emerging technology. You'll partner across Data Engineering, ML, and product-facing teams to harden agent infrastructure and keep it running at the standards our users expect.
Importantly, this is a platform engineering team. Beyond operating infrastructure, the team is responsible for building the APIs, SDKs, and platform capabilities that enable AI, Data, and Engineering teams to safely and efficiently consume agent infrastructure as a service. Success in this role requires thinking beyond infrastructure operations and toward developer experience, platform adoption, and long-term scalability.
Design, build, and operate the infrastructure layer supporting AI agent workflows in production
Ensure reliability, scalability, and observability of agentic systems across internal and external products
Design and develop platform services, APIs, SDKs, and self-service capabilities that allow engineering teams to easily consume AI infrastructure and agent platform services
Manage and maintain the compute, orchestration, and serving infrastructure powering model inference and agent execution
Implement robust monitoring, alerting, and incident response procedures tailored to AI/ML workloads
Utilize Infrastructure as Code (IaC) tools such as Terraform to provision and manage cloud (AWS) infrastructure components
Build and maintain CI/CD pipelines that support rapid, reliable deployment of AI services and agent workflows
Define and implement guardrails, failure handling, and recovery patterns specific to agentic and LLM-powered systems
Collaborate with AI and Data Engineering teams to translate experimental agent prototypes into hardened production systems
Manage containerized workloads using Kubernetes, ensuring efficient deployment, scaling, and orchestration of AI services
Implement access controls and security best practices across AI infrastructure environments
Document architecture, runbooks, and best practices to support knowledge sharing across the team
5+ years of experience as a Site Reliability Engineer, Infrastructure Engineer, Platform Engineer, or similar role in a production environment
Hands-on experience supporting ML infrastructure, model serving, or MLOps workflows in production
Experience building developer platforms, internal tooling, APIs, or SDKs consumed by engineering teams at scale
Strong understanding of platform engineering principles, including developer experience, self-service infrastructure, and API-driven platform design
Proficiency with Infrastructure as Code tools, particularly Terraform
Experience with containerization and orchestration, particularly Kubernetes and Docker
Solid understanding of cloud infrastructure, preferably AWS
Strong scripting skills (bash/shell) and proficiency in at least one programming language (Python preferred)
Experience designing and operating observability, monitoring, and alerting systems
Experience implementing incident response procedures and participating in on-call rotations
Strong collaboration skills working across data, AI, and engineering teams
High ownership mindset in a fast-moving, high-stakes production environment
Experience building or operating infrastructure for agent-based or LLM-powered systems
Familiarity with agent orchestration frameworks (e.g., LangGraph, CrewAI, or similar)
Background in data infrastructure, including familiarity with Airflow, Kafka, Spark, or data lake tooling
Experience with CI/CD pipelines and deployment automation for AI/ML workloads
Exposure to evaluation frameworks and model performance monitoring at scale
Experience working in fast-moving 0→1 environments or platform-building teams
Experience building SDKs, developer tooling, or internal platform products with a strong focus on usability and adoption
Experience with Cloudflare's cloud platform and product ecosystem, including networking, security, performance, and Zero Trust solutions
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.
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.
As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws.
Stay in the know
After you apply, unlock the direct contact details of the people who actually make the call. A quick follow-up makes you 5x more likely to land an interview.
Marcus Rivera
Chief Revenue Officer
ujet.cx
Jones Lang LaSalle
Resilinc
DigitalTolk
Nebius Group
Kraken
Kraken
Kraken
