3 months ago
Rome, ItalyStaff+
Responsibilities
- Architect and build agentic AI systems for finance workflows, including close, consolidations, variance analysis, management reporting, and ad-hoc analysis.
- Design multi-agent orchestration systems with guardrails, evaluations, and human-in-the-loop checkpoints.
- Identify finance automation opportunities and translate them into architectural blueprints, prototypes, and production roadmaps.
- Define standards for prompt engineering, tool integration, RAG, memory, agent observability, and solution reliability.
- Design and implement machine learning models for revenue, expense, cash-flow, driver-based forecasting, scenario modeling, and anomaly detection.
- Develop predictive, probabilistic, time-series, hierarchical, and causal approaches for FP&A planning.
- Embed AI-generated insights and narratives into the FP&A planning cycle.
- Establish backtesting, model monitoring, drift detection, and performance benchmarks.
- Run controlled pilots and measure impact on forecast accuracy, cycle time, and decision quality.
- Provide technical direction, hands-on prototypes, reference implementations, design reviews, and mentoring.
- Represent Finance in AI governance forums and contribute to enterprise AI strategy and standards.
- Establish responsible AI, model risk management, explainability, fairness, human oversight, data lineage, and control practices.
- Evaluate emerging AI capabilities and maintain a prioritized portfolio of finance AI use cases.
Requirements
- 10+ years of progressive experience in AI/ML, software engineering, or applied data science, including significant senior individual-contributor, principal, or staff-level architect experience.
- Demonstrated experience designing and shipping production AI systems, ideally including agentic AI, LLM-based applications, and ML for forecasting or planning.
- Hands-on expertise with foundation models and APIs, agent frameworks, RAG patterns, vector stores, orchestration tools, and ML libraries such as scikit-learn, PyTorch, TensorFlow, statsmodels, or Prophet.
- Strong software engineering fundamentals including Python, APIs, version control, testing, CI/CD, cloud platforms, and modern data stacks.
- Working knowledge of finance and FP&A concepts including budgeting, forecasting, variance analysis, driver-based planning, management reporting, ERP, EPM/CPM, data warehouses, and BI.
- Experience working with finance-relevant data such as general ledgers, sub-ledgers, headcount, sales pipelines, and operational drivers.
- Understanding of responsible AI, model risk management, security, privacy, audit, data quality, and data lineage in enterprise finance.
- Strong cross-functional communication, mentoring, technical leadership, and architectural decision-making capabilities.
Benefits
- Flexible hybrid work model associated with offices in Milan and Madrid.
- Opportunity to work in a rapidly scaling multinational company with an inclusive, informal environment.
- Autonomy, flexibility, learning opportunities, and regular feedback sessions.
- Modern central offices with fresh snacks, coffee including vegan options, and ergonomic workspaces.
- Team events including offsites, happy hours, company parties, and celebrations.
- Necessary equipment and workspace setup support for working effectively.
- Additional country-specific benefits based on local contracts and practices.
Tech Stack
Categories
About ShopFully
ShopFully builds a “drive-to-store” digital advertising platform that connects online shoppers with local retailers’ offers through its apps, websites, and a large publisher network. Retailers and brands use its AI-based targeting and ad products to promote weekly deals and measure in-store impact, paying for media and campaign services. Founded in 2012 and headquartered in Milan, it operates across 25 countries and reports connecting around 200 million shoppers for hundreds of retail clients.