[Remote] AI Agents Solutions Architect - Finance
Note: The job is a remote job and is open to candidates in USA. Kraken is a mission-focused company dedicated to accelerating global adoption of crypto and blockchain technology. They are seeking an AI Agents Solutions Architect - Finance to design and build an AI-native finance operating system, addressing operational complexities and automating finance processes across the organization.
Responsibilities
- 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
- 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
- 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
- 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
- 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
Skills
- 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
- 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
Company Overview
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