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Kraken, a leading crypto exchange founded in 2011 and trusted by over 10 million users globally, is seeking an AI Platform Engineer to own the technical layer of its internal AI platform. This role sits within Enterprise Transformation and focuses on building governance, enablement, and operational infrastructure for AI tooling deployed at scale across the organization.
You will design and build the technical integration surface for the AI platform, from API gateway to production runbooks. Key responsibilities include:
- Owning the governed integration gateway as an engineering surface, handling connector onboarding, authentication flows (OAuth, federated identity), reliability, and vendor escalation.
- Building internal tooling that extends platform capability: agent scaffolding, reusable prompt assets, evaluation harnesses for model changes, provisioning automation, and integrations with systems of record.
- Configuring and operating tiered spend controls across the AI estate—setting caps by role and tier, building alerting rules, managing exception queues, and running monthly vendor reconciliation.
- Implementing technical controls for data handling, retention, and model eligibility through identity integration, SSO, SCIM, role-based entitlement, and workspace configuration.
- Working directly with teams to unblock workflows and enable safe, effective use of AI tools.
- Running technical enablement: deep dives for tool rollouts, office hours for model releases, and authoring engineering-focused knowledge base material.
- Administering the enterprise AI estate end-to-end: model turn-ups, feature enablement, deprecation, provisioning queues, vendor configurations, and seat management.
The organization has already deployed tiered spend controls and a governed integration gateway in production, with a system inventory being built against regulatory obligations. The frontier now is capability—turning new protocols, APIs, and primitives into safe, usable tools for the broader organization.
REQUIREMENTS:
- Enterprise SaaS administration at 1,000+ seats, ideally including an AI or LLM platform.
- Demonstrated ability to build and ship working software (not just configure vendor products). Python or comparable language should be natural; version control, CI, containers, and secrets management are everyday tools.
- Experience integrating against LLM and SaaS APIs with working familiarity of agent and tool use patterns, including MCP or equivalent tool calling architectures.
- Working knowledge of identity and access: Okta or equivalent IdP, OAuth, SCIM, SSO, and federated machine identity.
- Operational discipline: intake queues, SLAs, runbooks, escalation hygiene, and instinct to document fixes.
- Genuine teaching ability—can explain technical capabilities in multiple ways to compliance, traders, and backend engineers.
- Clear written communication for technical documentation, runbooks, and policy pages.
- Judgment about what to build: ability to distinguish genuine organizational needs from demos that will be abandoned.
NICE TO HAVES:
- Experience standing up an internal developer or AI platform, including self-service and guardrail layers.
- Exposure to FinOps or software asset management.
- Experience with low-code or workflow automation platforms.
- Atlassian administration depth (Jira, Confluence, JSM).
- Familiarity with regulated industry audit and evidence work in financial services.
