Front Office Subject Matter Expert

About Behavox

Behavox is shaping the future for how businesses harness their most important raw material - data. Our mission is bold: Organize enterprise data into actionable information that protects and promotes the business growth of multinational companies around the world.

From managing enterprise risk and compliance to maximizing revenue and value, our data operating platform presents a widespread opportunity to build multilingual, AI/ML-based solutions that activate data for every function within a global enterprise.

Our approach is unique, and it’s validated by our customers who tell us to keep forging ahead because no one else is aggregating, analyzing, and acting on data to uncover opportunities or solve problems quite the way we are.

We are looking for fearless innovators who have an insatiable appetite for building what no one has built before.

About the Role

The Front Office Subject Matter Expert is an experienced individual contributor in the Subject Matter Expert (SME) team. The role is the primary owner of one or two related asset classes and makes sure that the Behavox Financial Data Model (BFDM) and the Unified Risk Taxonomy (URT) reflect how trading desks, venues and regulation actually work. The URT is the common language for risks across preventive controls (such as conflicts of interest and conduct) and detective controls (such as trade and communications surveillance).

Working with little day-to-day instruction, the role defines asset class data specifications, turns market abuse typologies into scenarios for Polaris, the Behavox trade surveillance product, and advises product, engineering and data science teams. It supports the revenue team in client meetings, demos and requests for proposal (RFPs) alongside a senior SME or the manager, but does not lead engagements with high-profile prospects or regulators on its own.

The role is AI-native: it works with AI agents and agentic workflows, not only chat assistants, specifying requirements for agent-based pipelines and validating their outputs through structured data models and Git-based workflows.

This is a remote friendly opportunity.

Typical background:

Experience: 5+ years of hands-on experience in a front office role, in market surveillance, or with front office data at an exchange, trading venue, market data provider or trading technology vendor.

Languages: English required; other languages a strong plus.

Agentic workflows: hands-on experience is a plus.

Location: open for a remote candidate within Italy.

What You'll Bring:

Asset class markets – Practitioner-level knowledge of at least one of: commodities and environmental products; digital assets and event contracts; fixed income and structured products; equities and funds; foreign exchange and money markets. This includes instruments, venues, trading conventions and pricing.

Front office workflows – Understanding of how execution, sales, research and risk functions operate on a trading desk, including order handling, quoting and hedging.

Market abuse typologies – Knowledge of behaviors such as insider dealing, spoofing and layering, wash trading, front running and benchmark manipulation, and how they appear in trade, order and market data.

Financial markets regulation – Working knowledge of trading conduct rules, such as the EU Market Abuse Regulation (MAR), the Markets in Financial Instruments Directive (MiFID II), and US rules of the Commodity Futures Trading Commission (CFTC) and the Securities and Exchange Commission (SEC).

Structured data modelling – Understanding of trade, order, market and reference data, their quality issues, and modelling concepts such as entities, schemas, validation rules and versioning.

What You'll Do:

Asset class data specification – Defines BFDM fields, schemas and validation rules for owned asset classes, and checks data outputs against them.

Surveillance scenario design – Turns market abuse typologies into Polaris risk scenarios, anchors them to regulatory enforcement cases, and validates their outputs with engineering and data science.

Risk taxonomy maintenance – Maps owned asset classes to URT risk situations and regulatory requirements, and keeps coverage current.

Client engagement support – Answers front office, data and surveillance questions in client meetings, demos and RFPs alongside the revenue team, and produces SME-reviewed collateral.

AI-native, agentic ways of working – Writes clear specifications for agent-based pipelines, reviews and validates their outputs, and contributes changes through Git-based workflows in GitLab.

What We Offer:

A truly global mission with a passionate community in locations all over the world

Huge impact and learning potential as our aspirations require bold innovation

Highly competitive compensation with 100% bonus pay already integrated

Benefits include individual career development budget for your learning and growth

Generous time-off policy and flexible work schedule

About Our Process:

We take Talent very seriously and we are building a community of extraordinary individuals working together in very high performing teams. We also know that the best Talent always has options so we believe that the process has to be a two way assessment - the company AND the candidate assessing the business needs alignment, the career next step alignment, and the cultural alignment.

During the process we will begin by exploring the core factors regarding salary and location along with core experience and skills and values alignment. We will then deep dive explore the critical technical competencies we have identified for the role, and then we will deep dive in behavioral competencies.

The most aligned candidate will then be asked to do a practical work task simulation activity so we can make sure that you will enjoy the kind of work the role requires, and this task will typically be presented and discussed with a group of colleagues and managers. Finally we will ask you to meet with a number of our senior leaders to make sure that you are making the most informed call possible.