About the Company
SmartStream is dedicated to transforming the financial services industry through innovative technology solutions. Our mission is to provide a cloud-hosted, multi-tenant data processing and reconciliation platform that leverages AI to enhance operational efficiency and user experience.
About the Role
The Product Manager will lead the transformation of SmartStream's cloud-hosted, multi-tenant data processing and reconciliation platform into an AI-first product. The mandate is to embed intelligent capabilities at every layer: data onboarding, lineage, transformation, reconciliation operations, and a co-pilot user experience that guides users through complex workflows using natural language and contextual AI.
Responsibilities
- Define and own the AI-first product roadmap, ensuring every capability data onboarding, transformation, matching, exception handling, and UX is designed around intelligent, model-driven behaviour.
- Lead the design of a co-pilot user experience, enabling users to interact with the platform through natural language, contextual suggestions, and AI-driven guided workflows.
- Work with data science and engineering teams to translate AI concepts (agentic workflows, ML scoring, anomaly detection, auto-rule generation) into shippable product features with clear human-in-the-loop approval mechanisms.
- Build and maintain strong relationships with enterprise clients, acting as a trusted product partner who deeply understands their data and reconciliation challenges.
- Lead structured discovery sessions interviews, workshops, and shadowing to uncover pain points, workflows, and unmet needs across the client base.
- Prototype early-stage concepts and ideas using low or high-fidelity mockups; present these to clients to gather structured feedback before any engineering investment is made.
- Triangulate findings across multiple clients and data sources to distinguish genuine patterns from one-off requests, ensuring roadmap decisions are well-evidenced.
- Instrument the product with behavioural analytics tooling (e.g. PostHog) to monitor how users navigate the platform, which AI features are adopted, and where drop-off or friction occurs.
- Define and track feature-level success metrics; regularly review usage data to validate that shipped features are delivering the intended value.
- Run structured experiments and analyse results to confirm or challenge product assumptions before committing to further investment.
- Use quantitative signals (usage trends, funnel data, error rates) alongside qualitative feedback (client interviews, support tickets) to build a complete picture of product performance.
- Shape platform architecture decisions relevant to AI delivery on a cloud-hosted, multi-tenant SaaS model including scalability, data isolation, and model serving considerations.
- Write clear user stories, acceptance criteria, and specs; manage a prioritised backlog in close collaboration with engineering.
- Define and track KPIs: AI feature adoption, match rates, break resolution time, onboarding efficiency, and user engagement.
Qualifications
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical field; or equivalent practical experience.
- 5 years in product management; experience in AI/ML products, cloud SaaS, data platforms.
- Demonstrable experience working with data science or ML engineering teams to ship production AI features.
- Hands-on experience with product analytics tooling in a live product environment.
- AI/ML literacy formal or self-directed learning demonstrating applied understanding of model types, evaluation, and ethical AI principles.
Required Skills
- Strong AI/ML product expertise able to define requirements for supervised/unsupervised models, LLM-based features, agentic workflows, and co-pilot UX patterns.
- Experience with LLM integration, prompt engineering, MCP Servers and building AI co-pilot interfaces.
- Technical background sufficient to engage credibly with engineers and data scientists understanding of cloud architecture, APIs, data pipelines, and SaaS platform design.
- Hands-on understanding of cloud-hosted, multi-tenant SaaS platforms including implications for data isolation, scalability, and feature rollout across tenants.
- Experience using product analytics tools (PostHog, Mixpanel, Amplitude, or similar) to monitor usage and validate feature value.
- Client-facing confidence able to run discovery sessions, present prototypes, and gather structured feedback from enterprise stakeholders.
- Min 5 years of product management experience with a track record of shipping AI or data-intensive software products.
Preferred Skills
- Good grasp of data reconciliation, data quality, or exception management concepts in an enterprise context.
- Knowledge of cloud platforms (AWS, Azure, or GCP) and modern data infrastructure (streaming, ETL/ELT, data warehouses).
- Experience in financial services, capital markets, or other data-intensive regulated industries.
- Familiarity with AI governance, responsible AI frameworks, or model explainability standards.
- Familiarity with SmartStream products or comparable platforms (Duco, Intellimatch).
Equal Opportunity Statement
SmartStream is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.
