AI Engineer - Financial Services

Job Title: AI Engineer – Financial Services Location: Hybrid - 3 Days onsite in Jersey City, NJ or Tampa, FL Employment Type: 6 Month Contract-to-Hire (Must be USC or Green Card Holder) - will not sponsor About the Role We are seeking a highly skilled AI Engineer with deep expertise in Large Language Models (LLMs), Natural Language Processing (NLP), and Python to support the modernization of post-trade financial infrastructure. This role will focus on applying AI to mission-critical services such as clearing, settlement, data enrichment, and digital asset integration within a highly regulated environment. You will help build AI-powered solutions that bridge traditional market systems with emerging digital platforms, driving efficiency, transparency, and risk mitigation across global financial services. Key Responsibilities • Design and implement Python-based frameworks for training, deploying, and monitoring AI models with a focus on LLMs and NLP. • Develop AI use cases for trade analytics, documentation summarization, anomaly detection, and conversational interfaces. • Integrate models into clearing, settlement, and trade repository systems, enhancing transparency and operational efficiency. • Support initiatives in digital assets and tokenization, ensuring AI solutions are interoperable with both traditional and next-generation platforms. • Collaborate with data engineering, risk, and compliance teams to ensure alignment with regulatory standards and data governance. • Optimize models for secure and scalable deployment in cloud-native environments and through standardized messaging frameworks (e.g., ISO 20022, APIs, sFTP). • Apply AI to extended-hours trading, real-time monitoring, and collateral management workflows, enabling greater market resiliency. • Stay current on developments in generative AI, digital asset infrastructure, and market structure transformation to drive innovation. Required Qualifications • Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or related field. • Experience in financial services infrastructure, such as clearing, settlement, risk, or trade data platforms. • Strong expertise in Python and relevant ML libraries (NumPy, Pandas, PyTorch, TensorFlow, Scikit-learn). • Hands-on experience with LLMs (e.g., GPT-based models, LLaMA, Falcon) and NLP frameworks (Hugging Face, spaCy, NLTK). • Proven track record deploying AI into production systems within regulated environments. • Familiarity with data privacy, lineage, and compliance requirements in financial markets.