Senior Software Engineer - AI Enablement Finance

Company: Kraken Locations: Canada, Ireland, Spain, Switzerland, Brazil, Poland, Mexico, South Africa, Argentina, United Arab Emirates, Romania, Czechia, Lithuania, Portugal, Cyprus, United Kingdom, and multiple locations Posted: Mar 26, 2026

Role Overview

You will serve as the primary architect and builder of the AI-native finance operating system at Kraken. This role spans two simultaneous horizons: deploying production automation now and redesigning the finance architecture for the long term.

Kraken's Global Finance team spans accounting, FP&A, treasury, tax, and finance operations across multiple regulated entities and 70+ countries, managing the financial infrastructure that underpins daily close, regulatory reporting, and crypto-native asset reconciliation.

Responsibilities

Assess and map Finance operations

• Evaluate how financial work currently flows across the organization, including close, reconciliations, treasury, reporting, controls validation, and audit preparation.
• Identify capability gaps, manual bottlenecks, and integration failure points across systems including NetSuite, BlackLine, Kyriba, Fireblocks, and Lukka.
• Benchmark current operations against best-in-class practices and emerging AI capabilities to build the Finance automation roadmap, prioritized by operational leverage and regulatory risk.
• Work directly with accounting, FP&A, treasury, and finance operations teams to translate process pain points into buildable automation requirements.

Architect the agentic finance platform

• Design the long-term architecture for an AI-native finance operating system.
• Define how agentic systems interact with financial infrastructure, data pipelines, and control and reporting frameworks.
• Evaluate Kraken's existing finance systems stack from first principles, including platforms and the interfaces and data flows between them.
• Identify opportunities to simplify the stack, reduce manual intervention, and define a scalable target architecture.
• Build an agentic finance layer that runs alongside the existing stack today, automating workflows while defining the migration path toward a more scalable, AI-native architecture over time.

Build and deploy production finance automation

• Deploy production-grade agentic workflows that automate finance operations, including reconciliations, close processes, audit and reporting preparation, treasury monitoring, financial analytics, and controls validation.
• Build using modern AI tooling including Claude and Anthropic APIs, Python-based orchestration, n8n or equivalent workflow engines, and MCP or similar agent coordination layers.
• Integrate internal and external systems by connecting APIs, data sources, and tools into unified automated workflows that deliver real operational leverage.
• Maintain human oversight where appropriate.
• Design for auditability and control integrity, not just efficiency.

Own AI governance for Finance

• Establish guardrails that allow automation and agent behavior to operate safely in a SOX-regulated financial environment.
• Define which controls are maintained, which are redesigned, and how workflow scope preserves control integrity.
• Build frameworks covering data classification, auditability, human-in-the-loop checkpoints, failure detection, rollback mechanisms, regulatory compliance, and audit-ready design documentation.
• Classify all automation builds by risk tier before work begins.
• Ensure no build goes to production without a named Process Owner, documented data flows, access controls, and audit logging confirmed.
• Serve as the Finance domain representative in Kraken's Automate Everything Center of Excellence, contributing to governance standards and cross-functional build alignment.

Build the foundation for AI-native Finance

• Create reusable frameworks, workflow templates, and documentation so future Finance team members can safely build on top of the platform without relying on a single specialist.
• Train finance professionals on AI-assisted tools and workflows deployed in production.
• Drive adoption and operational independence, not just delivery.
• Build metrics, dashboards, and performance frameworks to measure efficiency gains, cost reduction, risk outcomes, and ROI from automation and AI initiatives.
• Provide leadership reporting on operational improvements, risk posture, and the finance platform roadmap.

Required Qualifications

• Proven track record designing, deploying, and scaling agentic AI systems in production environments used by others, not just experimentation or internal demos.
• Deep understanding of LLM orchestration, multi-agent system design, and the failure modes of autonomous AI workflows in high-stakes operational environments.
• Strong systems architecture capability, with the ability to move from discovery to design to build to deployment to optimization without relying on external consultants.
• Hands-on proficiency with modern AI automation tooling: Claude/Anthropic APIs, Python-based orchestration, n8n or equivalent workflow engines, MCP or similar agent coordination layers.
• Strong domain knowledge of finance operations including close processes, reconciliations, treasury, financial reporting, and controls in a regulated environment.
• Experience deploying automation in a SOX-regulated or equivalent compliance environment, with demonstrated understanding of which controls must be preserved and how to design automation that maintains audit integrity.
• Ability to translate finance and business requirements into technical roadmaps and scalable operational solutions.
• Strong communication skills to bridge finance, technical, and business teams while influencing senior stakeholders and driving cross-functional alignment.
• Comfortable operating in fast-paced, ambiguous environments with a high level of ownership and bias toward execution.

Preferred Qualifications

• Experience with finance systems or equivalent enterprise platforms such as NetSuite, BlackLine, Kyriba, Fireblocks, or Lukka.
• Background as a Head of Product or Head of Engineering at an AI-native company, AI systems architect, or founder or early engineer at an agentic infrastructure company.
• Familiarity with crypto-native financial infrastructure including digital asset custody, on-chain reconciliation, and blockchain-based accounting workflows.
• Experience in high-velocity or resource-constrained environments such as a startup, PE-backed company, or an understaffed finance team where you had to build the system yourself.
• Familiarity with data privacy, information governance, or compliance systems in a financial services context.
• Experience managing vendor relationships and procurement for finance technology platforms.

Application Notes

• Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis.
• 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.
• The company considers qualified applicants with criminal histories for employment in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.
• Candidates may be asked to complete job-related skills or work-style assessments as part of the hiring process.