We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. You’ll join a collaborative team where your ideas and skills help shape intelligent, data-driven products that power business innovation. As part of a diverse and inclusive environment, you’ll work alongside talented engineers and data scientists, deepening your expertise in Python and machine learning. If you’re passionate about solving complex problems and advancing technology, you’ll find strong support and growth opportunities here.
Job Summary
As a Software Engineer III in Corporate Technology’s AI, ML & Data Platforms team, you will design and deliver secure, stable, and scalable technology solutions that support the firm’s data and artificial intelligence objectives. You will work as a valued member of an agile team, tackling technical challenges across multiple areas and contributing to end-to-end delivery. You will help strengthen engineering practices through thoughtful design, strong coding standards, and continuous improvement, while fostering a culture of inclusion and respect.
Job Responsibilities
- Execute software solutions through design, development, and technical troubleshooting, applying creative thinking to break down complex technical problems
- Create secure, high-quality production code in Python and maintain algorithms that integrate effectively with supporting data and machine learning systems
- Produce architecture and design artifacts for complex applications and ensure design constraints are reflected throughout software development
- Gather, analyze, and synthesize large, diverse datasets to develop visualizations and reporting that support continuous improvement of software applications and systems
- Proactively identify hidden problems and patterns in data and apply those insights to improve coding hygiene and system architecture
- Collaborate with data scientists and platform engineers to support the development and deployment of machine learning and artificial intelligence solutions
- Contribute to software engineering communities of practice and participate in events that explore new and emerging technologies
- Support a team culture grounded in diversity, opportunity, inclusion, and respect
- Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation
Required Qualifications, Capabilities, and Skills
- Formal training or certification on software engineering concepts and proficient applied experience
- Proficiency in Python for building scalable backend services and data-intensive applications
- Hands-on experience in system design, application development, testing, and operational stability
- Experience developing, debugging, and maintaining production code using modern programming languages and database querying languages in a large-scale environment
- Working knowledge of the Software Development Life Cycle
- Understanding of agile methodologies and practices, including CI/CD, application resiliency, and security
- Demonstrated knowledge of software applications and technical processes within a technical discipline such as cloud, artificial intelligence, machine learning, or data engineering
- Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, testing, troubleshooting, or documentation) with demonstrated ability to critically evaluate and validate AI-generated outputs
- Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations
Preferred Qualifications, Capabilities, and Skills
- Familiarity with machine learning frameworks and tools used in model development and deployment pipelines
- Exposure to cloud-based infrastructure and data services
- Knowledge of traditional machine learning and large language model serving in production environments
- Familiarity with modern front-end technologies or data visualization tools
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