Senior Software Engineer - AI Enablement Finance

Kraken’s Global Finance team is the operational backbone of one of the world’s most trusted and longest-standing crypto exchanges. The team spans accounting, FP&A, treasury, tax, and finance operations across multiple regulated entities and 70+ countries, managing the financial infrastructure that underpins everything from daily close to regulatory reporting to crypto-native asset reconciliation.

As financial complexity grows with Kraken’s global footprint, this role architectures and provides hands-on building to scale growth. Finance operations at a globally regulated crypto exchange managing close cycles, reconciliations, reporting, treasury monitoring, and controls validation all generate substantial manual effort tied to critical financial and regulatory obligations. Errors carry audit, SOX, security ,and regulatory consequences.

The Opportunity

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. Responsibilities span five core areas:

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: 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. 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 that 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.

• 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: able 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 communicator who can 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.

Nice to Have

• Experience with Finance systems stack or equivalent enterprise platforms: 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: 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.

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., 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.