Software Engineer III - AI/ML Developer
On-sitePlano, Texas, United States
Job Summary
Execute creative software solutions through design, development, and technical troubleshooting of multiple components within the firm's state-of-the-art technology products. Develop secure, high-quality production code while reviewing and debugging work from others, applying enterprise-authorized AI-assisted engineering practices to improve code quality and delivery speed. Lead evaluation sessions with external vendors and internal teams to probe architectural designs and drive outcomes-oriented probing of technical credentials. Gathers, analyzes, and draws conclusions from large, diverse data sets to identify problems and contribute to decision-making in service of secure, stable application development. This role sits within the Consumer & Community Banking division, requiring proficiency in Python, TensorFlow, PyTorch, and cloud-based ML platforms like AWS SageMaker or GCP AI Platform. Candidates must demonstrate hands-on experience building and maintaining machine learning platforms, leading effective use of approved AI-assisted development tools, and adhering to responsible AI use in engineering workflows.
Required Qualifications
- Formal training or certification on software engineering concepts
- 3+ years applied experience
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Hands-on experience building, deploying, and maintaining machine learning platforms or infrastructure
- Proficiency in Python and one or more ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
- Experience with data processing frameworks and tools (e.g., Spark, Pandas, SQL)
- Practical experience with cloud-based ML platforms (e.g., AWS SageMaker, GCP AI Platform, Azure ML) or on-prem ML infrastructure
- Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations
- experience coaching engineers on safe, compliant adoption within delivery practices
- Proficient in all aspects of the Software Development Life Cycle
- Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- In-depth knowledge of the financial services industry and their IT systems
- Practical cloud native experience
Desired Qualifications
- Familiarity with Databricks for scalable data engineering and ML platform integration
- Experience working with Snowflake for cloud-based data warehousing and analytics
- Exposure to Snorkel AI for programmatic data labeling and training data management
- Experience with containerization and orchestration tools (e.g., Docker, Kubernetes, Airflow)
- Familiarity with feature stores, model registries, and ML metadata management
- Experience with infrastructure-as-code tools (e.g., Terraform, CloudFormation)
- Experience with RESTful APIs and microservices architectures
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