Market Risk Eng, Dallas, Vice President, AI Engineer

About the role

We are seeking an Engineer with 9+ years of experience to join the Market Risk Platform team. You will work with a team of talented engineers to drive the build & adoption of common tools, platforms, and applications. The team builds solutions that are offered as a software product or as a hosted service. We are a dynamic team of talented developers and architects who partner with business areas and other technology teams to deliver high-profile projects using a range of technologies (Java, Cloud computing, HDFS, Spark, S3, ReactJS, Sybase IQ, and others).

A glimpse of the interesting problems we engineer solutions for includes acquiring high-quality data, storing it, performing risk computations in a limited amount of time using distributed computing, and making data available to enable actionable risk insights through analytical and responsive user interfaces.

Responsibilities

• Build internal and external reporting for the output of risk metric calculations using data extraction tools (e.g., SQL) and data visualization tools (e.g., Tableau).
• Utilize web development technologies to facilitate application development for front-end UIs used for risk management actions.
• Develop software for calculations using databases like Snowflake, Sybase IQ, and distributed HDFS systems.
• Design and support batch processes using scheduling infrastructure for calculation and distributing data to other systems.
• Design, develop, and deploy machine learning and AI models to support market risk metrics, stress scenarios, early-warning indicators, and forecasting.
• Build end-to-end AI pipelines, including data ingestion, feature engineering, model training, validation, deployment, and monitoring.
• Partner with risk managers and quantitative teams to translate regulatory and business requirements into AI-driven solutions.
• Optimize agents' performance, scalability, and reliability in distributed and cloud-based environments.
• Mentor junior engineers and contribute to code reviews, design discussions, and architecture decisions.

Requirements

• 9+ years of professional experience as an Engineer in a production environment.
• Exposure to distributed computing frameworks and workflow orchestration tools (e.g., Airflow).
• Experience working with large, structured datasets using SQL and distributed data platforms (cloud data warehouses).
• Strong proficiency in Python and experience with ML/AI libraries such as PyTorch or similar.
• Hands-on experience integrating LLM models using agents and developing monitoring and observability tools for those agents is a plus.
• Experience developing agents using Google ADK or Lang Graph frameworks and deploying them on AWS is a plus.
• Exposure to AWS services like S3, ECS, MWAA, Lambda, and DynamoDB is a plus.

Benefits

• Opportunity to work at the intersection of AI, engineering, and market risk at a global scale.
• High-impact role influencing how the firm measures and manages market risk under stress.
• Collaborative environment with exposure to senior risk managers, quants, and technology leaders.
• Ongoing learning, development, and career progression within the Liquidity and Engineering organizations.