3 months ago
Rome, ItalyStaff+
Responsibilities
- Architect and build agentic AI systems to automate finance workflows, including close, consolidations, variance analysis, management reporting, and analytical requests.
- Design multi-agent orchestration systems with planners, retrievers, executors, reviewers, guardrails, evaluations, and human-in-the-loop checkpoints.
- Create architectural blueprints, prototypes, and production roadmaps for high-impact Finance automation opportunities.
- Define standards for prompt engineering, tool integration, RAG, memory, and agent observability.
- Partner with Engineering, IT, and Security to productionize agents while addressing identity, access, secrets management, audit logging, and change control.
- Design and implement machine learning models for revenue, expense, cash flow, driver-based forecasting, scenario modeling, and anomaly detection.
- Establish backtesting, model monitoring, drift detection, performance benchmarks, and experimentation practices.
- Serve as the senior AI technical voice within Finance by setting direction, reviewing designs, and providing reference implementations.
- Mentor finance analysts, FP&A partners, and engineering teams on AI, ML, and responsible-use patterns.
- Represent Finance in AI governance forums and establish responsible AI, model risk, explainability, human oversight, data lineage, and control practices.
- Evaluate emerging AI capabilities through structured pilots and maintain a portfolio of Finance AI use cases.
Requirements
- 10+ years of progressive experience in AI/ML, software engineering, or applied data science, including significant experience as a senior individual contributor, principal, or staff-level architect.
- 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, and Prophet or equivalents.
- 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, with attention to data quality and lineage.
- Working understanding of responsible AI, model risk management, security, privacy, and audit considerations for enterprise finance.
- Ability to influence technical direction, mentor cross-functional partners, and translate finance problems into practical production solutions.
Benefits
- Flexible hybrid work model with offices in Milan and Madrid.
- Learning opportunities and regular feedback sessions.
- Modern central offices with fresh snacks, coffee, vegan options, and ergonomic setups.
- Team events including offsites, happy hours, company parties, and celebrations.
- Necessary equipment provided for effective remote or office work.
- Additional country-specific benefits based on local contracts and practices.
- Inclusive multinational environment with autonomy and flexibility.
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.