X, formerly known as Twitter, is strengthening its push into cryptocurrency by posting jobs for finance and crypto experts to improve how its AI systems understand and operate in financial markets.
The move highlights the company’s intent to build deeper expertise in digital assets, trading, and risk, signaling a strategic shift toward developing AI models capable of real-world financial reasoning in the fast-evolving digital economy, says GlobalData.
Sherla Sriprada, business fundamentals analyst at GlobalData, comments: “The company’s efforts to hire experts in areas related to AI, digital assets, quantitative trading, and risk management are designed to guide model development, address problems in crypto and financial markets, and respond to the ongoing changes in regulatory requirements.
“This approach indicates a focus on enhancing internal expertise in finance and technology, as well as improving AI model performance.”
X recently posted a “Finance Expert – Crypto” role to help advance its frontier AI models by providing high-quality annotations, evaluations, and expert reasoning using proprietary labeling tools. The role involves close collaboration with technical teams on the development and refinement of new AI tasks, with a particular focus on cryptocurrency and digital asset markets.
The role also looks at leading advancements at the intersection of AI and crypto trading. This position requires domain knowledge to solve complex problems in quantitative crypto strategies — including on-chain analysis, DeFi protocols, perpetual futures and derivatives trading, cross-exchange arbitrage, market microstructure in fragmented venues, MEV-aware execution, machine learning for crypto alpha signals, and portfolio/risk management in high-volatility 24/7 markets.
While this is X’s only crypto-specific role, the company has also posted related roles such as “Finance Expert – Quantitative Trading”. This position is to guide models on how quantitative traders reason, model markets, evaluate signals, manage risk, and interact with complex financial data and systems. This involves providing high-quality data in various formats (text, voice, video), writing detailed annotations, critiquing model outputs, recording audio explanations, and occasionally participating in structured video sessions.
Another similar role, “Finance Expert – Risk”, is responsible for the selection and rigorous resolution of complex risk-related problems — including market risk modeling, credit and counterparty risk, liquidity and funding risk, operational and model risk, stress testing & scenario analysis, value at risk (VaR)/expected shortfall (ES), risk attribution, capital allocation (economic/regulatory), and enterprise-wide risk frameworks under regulatory regimes (Basel, Dodd-Frank, IFRS 9, etc.).
Sriprada concludes: “As digital assets reshape global finance, companies that combine domain expertise with AI capabilities will gain a decisive edge, positioning themselves not just as technology players, but as future architects of the digital financial ecosystem.”