Enterprise AI Platform Engineer

Kraken; United States; Remote; USD 180,000 - 240,000; Full time

Job summary

Kraken is building an internal AI platform to power open finance capabilities. The role focuses on designing the technical layer from surface to production runbooks and owning the governed integration gateway with OAuth, federation, and reliability.

You will create internal tooling, refine spend controls, and implement data-handling policies across the AI estate. We seek an experienced Enterprise SaaS administrator with strong Python skills, API integration experience, and deep knowledge of

Qualifications

• Enterprise SaaS administration at 1,000+ seats, ideally including an AI or LLM platform.
• Demonstrated ability to build and ship working software; Python or a comparable language should be natural to you.
• 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 an equivalent IdP, OAuth, SCIM, SSO, and federated machine identity.
• Operational discipline: you understand intake queues, SLAs, runbooks, escalation hygiene, and the instinct to document a fix the first time you make it.
• Genuine teaching ability: you can explain a technical capability three different ways on the same day to compliance, traders, and backend engineers.
• Clear written communication for technical documentation, runbooks, and policy pages.
• Judgment about what to build: you can tell the difference between a capability the organization actually needs and a demo that will be abandoned in a month.

Responsibilities

• Design and build the technical layer of the AI platform, from integration surface to production runbook.
• Own the governed integration gateway as an engineering surface. You'll handle connector onboarding, authentication flows including OAuth and federated identity, reliability, and vendor escalation when things break.
• Build internal tooling that extends the platform. Think agent scaffolding, reusable skills and prompt assets, evaluation harnesses for model changes, provisioning automation, and integrations between AI tooling and your systems of record.
• Configure and operate tiered spend controls across the AI estate. Set caps by role and tier, build alerting rules, manage exception queues, run monthly reconciliation against vendor commitments, and eliminate the current single author risk in cap automation.
• Implement the technical controls behind policy on data handling, retention, and model eligibility. This means identity integration, SSO and SCIM, entitlement by role and tier, and workspace configuration where retention terms differ by model class.
• Work directly with teams to unblock them. Sit with them, understand the workflow, build or configure the thing that enables them to get real leverage from the tools.
• Run technical enablement. Deep dives for tool rollouts, office hours for model releases, and authority over the engineering detail in knowledge base material.
• Administer the enterprise AI estate end to end. Model turn ups, feature enablement, deprecation, provisioning queue, vendor configurations, and seat true ups.

Skills

Python

LLM integration

API design

Identity and access

Operational discipline

Technical teaching

Cloud platforms

Security

Tools

CI/CD

Containers

Secrets management

Version control

Okta

OAuth

SCIM

Federated identity

Job description

Kraken is building an internal AI platform to power open finance capabilities. The role focuses on designing the technical layer from surface to production runbooks and owning the governed integration gateway with OAuth, federation, and reliability.

You will create internal tooling, refine spend controls, and implement data-handling policies across the AI estate. We seek an experienced Enterprise SaaS administrator with strong Python skills, API integration experience, and deep knowledge of