AI Product Owner - Finance Automation (all genders)
Role details
Job location
Tech stack
Job description
Serrala is evolving from traditional finance automation toward AI-enabled and agent-driven finance execution.
The AI Product Owner is responsible for translating finance domain problems into high-value, AI-powered product capabilities-from intelligent assistance to semi-autonomous and autonomous workflows. This role sits at the intersection of Finance domain expertise, Product Management, and AI capabilities.
The AI Product Owner owns the problem space, value definition, and delivery prioritization for AI use cases within Serrala's finance automation portfolio, ensuring every AI feature delivers measurable customer outcomes, aligns with governance and trust requirements, and can be productized at scale. Your Day to Day:
- Own AI-driven product capabilities for finance workflows (e.g. AP, AR, Cash, Payments, Treasury).
- Identify where AI can reduce manual work, improve exception handling, and support better finance decisions.
- Define and prioritise AI use cases based on business value, feasibility, and scalability.
- Translate finance requirements into clear product specifications for engineering and platform teams.
- Work closely with engineering and central platform teams to ensure secure, scalable, and maintainable solutions.
- Ensure finance-grade standards for trust, governance, auditability, and human oversight.
- Track outcomes and continuously improve based on data, KPIs, and user feedback., Serrala does not accept agency resumes. Please do not forward resumes to our job alias, Serrala employees or any other organization location. Serrala is not responsible for any fees related to unsolicited resumes.
Requirements
Language(s): English (C1/ C2), * 5+ years of experience as a Product Manager or Product Owner in enterprise software.
- Strong understanding of finance operations (e.g. AP, AR, Payments, Cash, Treasury, Credit, Disputes).
- Proven ability to structure complex domain problems into clear product requirements.
- Solid understanding of AI concepts and their practical application, e.g., ML vs. rules, LLMs, agentic workflows, human-in-the-loop (no coding required).
- Experience working with cross-functional teams (engineering, data, UX, compliance, go-to-market).
- Confidence in making prioritisation decisions in complex or uncertain environments.
- Experience with data-driven or AI-enabled products, ideally in regulated domains.
- Familiarity with ERP-centric or SAP-embedded environments.
- Track record of defining outcome-based KPIs and linking features to business value.
