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Behavox is building a data operating platform that helps multinational enterprises organize and act on enterprise data for risk management, compliance, and revenue optimization. The company specializes in multilingual, AI/ML-based solutions for financial services, particularly in trade surveillance and market abuse detection.
As a Front Office Subject Matter Expert, you will be an experienced individual contributor owning one or two related asset classes within the Subject Matter Expert team. You will be the primary owner ensuring that the Behavox Financial Data Model (BFDM) and Unified Risk Taxonomy (URT) accurately reflect how trading desks, venues, and regulation actually operate. The URT serves as the common language for risks across preventive controls (conflicts of interest, conduct) and detective controls (trade and communications surveillance).
Working with minimal day-to-day instruction, you will define asset class data specifications, translate market abuse typologies into scenarios for Polaris (Behavox's trade surveillance product), and advise product, engineering, and data science teams. You will support the revenue team in client meetings, demos, and RFPs alongside senior SMEs or management, though you will not independently lead high-profile prospect or regulator engagements.
This role is AI-native: you will work with AI agents and agentic workflows—not just chat assistants—specifying requirements for agent-based pipelines and validating outputs through structured data models and Git-based workflows.
Key responsibilities include:
- Defining BFDM fields, schemas, and validation rules for owned asset classes, and validating data outputs
- Converting market abuse typologies into Polaris risk scenarios anchored to regulatory enforcement cases
- Mapping asset classes to URT risk situations and regulatory requirements, maintaining current coverage
- Answering front office, data, and surveillance questions in client engagements and producing SME-reviewed collateral
- Writing clear specifications for agent-based pipelines, reviewing and validating outputs, and contributing changes via Git-based workflows in GitLab
Requirements:
- 5+ years of hands-on experience in a front office role, market surveillance, or front office data at an exchange, trading venue, market data provider, or trading technology vendor
- Practitioner-level knowledge of at least one asset class: commodities and environmental products; digital assets and event contracts; fixed income and structured products; equities and funds; or foreign exchange and money markets (including instruments, venues, trading conventions, and pricing)
- Understanding of front office workflows: execution, sales, research, and risk functions on trading desks, including order handling, quoting, and hedging
- Knowledge of market abuse typologies (insider dealing, spoofing, layering, wash trading, front running, benchmark manipulation) and how they appear in trade, order, and market data
- Working knowledge of trading conduct rules: EU Market Abuse Regulation (MAR), Markets in Financial Instruments Directive (MiFID II), US CFTC and SEC rules
- Understanding of structured data modeling: trade, order, market, and reference data; data quality issues; and modeling concepts (entities, schemas, validation rules, versioning)
- Fluent English; other languages a strong plus
- Hands-on experience with agentic workflows is a plus
- Open to remote work within Italy
