Sr. Software Engineer - Analytics & AI

At U.S. Bank, we’re on a journey to do our best. Helping the customers and businesses we serve to make better and smarter financial decisions and enabling the communities we support to grow and succeed.  We believe it takes all of us to bring our shared ambition to life, and each person is unique in their potential. A career with U.S. Bank gives you a wide, ever-growing range of opportunities to discover what makes you thrive at every stage of your career. Try new things, learn new skills and discover what you excel at—all from Day One.

Job Description

This position will be responsible for the analysis, design, testing, development and maintenance of best in class software experiences. The candidate is a self-motivated individual who can collaborate with a team and across the organization. The candidate takes responsibility of the software artifacts produced adhering to U.S. Bank standards in order to ensure minimal impact to the customer experience. The candidate will be adept with the agile software development lifecycle and DevOps principles.

Essential Responsibilities:

• Solution Design & Development:Architect and develop enterprise-grade applications using Azure Synapse Analytics, Azure Databricks, Azure Data Factory, and Azure Stream Analytics.Integrate AI capabilities using Azure Machine Learning, Azure Cognitive Services, Azure AI Search, and Azure OpenAI Service.

• Data Engineering & AI Integration: Build and optimize data pipelines for ingestion, transformation, and orchestration.Implement machine learning models and AI-driven features for predictive analytics and automation.

• Cloud & DevOps: Deploy microservices and containerized solutions using Docker, Kubernetes, and CI/CD pipelines. Ensure compliance with security, governance, and performance standards.

• Global Collaboration: Coordinate with offshore engineering teams for development, testing, and support activities. Provide technical guidance and ensure alignment across distributed teams.

• Release & Deployment Management: Oversee release planning, weekend deployments, and production rollouts with minimal downtime. Manage version control, rollback strategies, and post-release validation.

• Continuous Improvement: Stay current with emerging Azure technologies in analytics and AI; drive innovation and best practices.

Basic Qualifications
- Bachelor’s degree, or equivalent work experience
- Five to six years of relevant experience

Preferred Skills/Experience

• Programming Languages: Proficiency in Python, Java, Scala, and SQL for data processing and application development.

• Cloud & Analytics Platforms: Deep expertise in Azure Synapse Analytics, Azure Databricks, Azure Data Factory, Azure Stream Analytics, and Azure Data Explorer.

• AI & Machine Learning: Experience with Azure Machine Learning, Azure Cognitive Services, Azure AI Search, and Azure OpenAI Service for building intelligent applications.

• Knowledge of ML model lifecycle, including training, deployment, and monitoring.

• Data Engineering: Strong skills in ETL pipelines, data warehousing, real-time streaming, and big data frameworks (Spark, Hadoop).

• DevOps & CI/CD: Expertise in Azure DevOps, Git, Docker, Kubernetes, and automated deployment pipelines.

• Architecture & Design: Ability to design cloud-native, microservices-based architectures with scalability and security in mind.

• Testing & Quality: Familiarity with unit testing, integration testing, and performance testing for analytics and AI workloads.

Location Expectations

The role offers a hybrid/flexible schedule, which means there's an in-office expectation of 3 or more days per week and the flexibility to work outside the office location for the other days.

If there’s anything we can do to accommodate a disability during any portion of the application or hiring process, please refer to our disability accommodations for applicants.

Benefits: 

Our approach to benefits and total rewards considers our team members’ whole selves and what may be needed to th