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Niche payments plus agentic AI architecture requirements and seniority reduce applicant competition.
Strong payments domain and regulatory expertise required, limiting transferability across industries.
Requires production-grade ML/LLM orchestration, payments domain expertise, and governance, enforcing strict technical filters.
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Own the long-term architecture and evolution of an AI-native Payments Operating System, focusing on automation and control integrity in regulated financial environments.
Design and implement agentic payment layers and reusable frameworks that automate workflows and integrate with existing payment systems to enable a gradual migration to future architectures.
Lead AI governance by classifying automation risk tiers, ensuring documented process ownership, data flows, access controls, and audit logging while collaborating across technical, compliance, and product teams.
Experience deploying production-grade AI or agentic systems, including LLM orchestration and multi-agent systems.
Strong skills in AI orchestration technologies, such as Spring AI or Python-based orchestration, workflow engines (e.g., n8n), and AI APIs like Anthropic/Claude.
Demonstrated architectural experience in scalable, future-ready platforms with end-to-end ownership from discovery through optimization.
Work Experience Required: Not explicitly mentioned in the JD. Notice Period: Not explicitly mentioned in the JD.
Experienced in operating at the intersection of payments domain and AI engineering, with strong capability to translate business and finance requirements into technical roadmaps.
Skilled in AI governance and risk management in regulated financial environments, ensuring control integrity and compliance across automation solutions.
Thrives in fast-paced, ambiguous settings with high ownership and execution bias, effectively bridging business and engineering domains.