Senior Software Engineer – Platform & Infrastructure

Group Details

Tradeweb is seeking a Data Analytics and AI, Development and Operations Senior Engineer to join its Internal Audit Department, supporting the Data Analytics and AI Development and Operations Lead in building and maintaining scalable audit technology solutions. The team member will own the development of the internal audit tools front to back. This role plays a critical part in operationalizing AI/ML models and data workflows that enhance the efficiency and effectiveness of business and technology audits.

We are seeking a Full-Stack Systems Engineer with strong coding experience to support the deployment and operationalization of our front end self service and the back end data pipelines and AI/ML models integration to enable the audit software platform. This hands-on role combines practical engineering with implementation rigor, focusing on converting audit prototypes into reliable, reusable applications. Core responsibilities include building and maintaining data pipelines, assisting with model deployment workflows, and contributing to system reliability through CI/CD, monitoring, and automation. The engineer will work closely with audit professionals to streamline repetitive tasks, promote software reusability, and uphold operational excellence. This role is the opportunity to shape the system architecture and have a lasting impact as this role plays a critical part in executing the technical foundation of data, ML, and infrastructure components.

Success in this role will be measured by the strength and reliability of the data pipelines and the usability of the audit software platform. On the data side, key metrics include confidentiality, accessibility, and integrity. On the software side, success will be defined by a low-touch, intuitive user interface that enables self-service capabilities for auditors, minimizes manual intervention, and maintains high uptime and responsiveness that integrates within Tradeweb architecture. Every engineering effort should contribute to a secure, seamless, and resilient platform that empowers audit teams to operate efficiently and independently.

Job Responsibilities

• Implement reusable, production-grade audit software components.
• Implement components of the system architecture for scalable audit automation and AI platforms, based on guidance from the Lead.
• Build and maintain robust data pipelines and AI/ML workflows to support audit analytics and reporting.
• Deploy and operationalize machine learning models with a focus on reliability, performance, and maintainability.
• Ensure operational stability through CI/CD automation, system monitoring, and proactive troubleshooting.
• Collaborate with India’s team.
• Contribute to Buy vs Build evaluations by providing technical feasibility assessments and implementation effort estimates.
• Drive best practices in software development, testing, deployment, and documentation.
• Understand and leverage Tradeweb’s technology stack to maximize integration and reduce the platform technology risk/debt.
• Apply a pragmatic, ROI-driven approach to the technology selection—leveraging advanced solutions only when justified.
• Promote a “parsimonious” approach to data load – only retrieving and storing the information required.
• Facilitate the compliance of the data stack with the Data Policies of Tradeweb.
• Document system designs, deployment processes, and operational procedures for long-term sustainability.

Qualifications

Must Have:

• 5 plus years of proven experience in cross-regional collaboration in the financial industry.
• Bachelor’s or Master’s degree in System Engineering, Computer Science, Data Engineering, Information Systems, or a related field.
• Proficiency in Python, SQL, and one or more modern programming languages.
• Experience with data pipeline orchestration tools, rest API and ETL frameworks (Snowflakes).
• Strong Linux knowledge and familiar with both cloud and on local deployments
• Strong network and cyber engineering knowledge (to allow for a reliable architecture)
• Familiarity with ML model deployment.
• Strong UI/UX development and deployment skills

Expected by default:

• Excellent communication skills and a high degree of autonomy, with the ability to collaborate effectively both the local team and with a core team based in New York and operate seamlessly across time zones.
• Expertise in software development best practices, including modular design, code reusability, testing, and documentation.
• Hands-on experience with SQL and NoSQL databases, data modeling, and performance optimization for audit and analytics use cases.
• Wide range of technology exposure including:
  • multiple programming language : Python, C++, Javascript, VBA
  • available data tools for visualization Tableau, PowerBi, HTML
  • databases: SQL, Snowflakes, databricks
  • AI/Ml platform : KNIME, ALTERYX
  • code and no code development tools