Principal Software Engineer

Job Summary:

We are seeking a highly skilled and experienced Principal AI/ML and Gen AI Engineer to join our dynamic team at CCB COSMIC (CCB Operational Systems for Machine Intelligence and Cognition). The ideal candidate will possess a strong foundation in AWS, AI/ML, Databricks, and the Gen AI ecosystem. This role is primarily focused on scaling infrastructure and platforms from a serving and fine-tuning standpoint. The candidate should also have extensive experience in LLM Ops and the productionalization of Gen AI use cases.

Key Responsibilities:

• Design, implement, and scale AI/ML infrastructure and platforms on AWS to support serving and fine-tuning of models.
• Collaborate with cross-functional teams to ensure seamless integration and deployment of AI/ML solutions.
• Develop and optimize machine learning models and algorithms to meet business objectives.
• Stay updated with the latest advancements in AI/ML and Gen AI technologies and incorporate them into the organization's strategy.
• Architects and governs agentic AI-enabled engineering workflows (using enterprise-authorized tools within the work environment) to improve delivery speed, code quality, and operational outcomes at scale (e.g., AI-driven PR review assistance, test generation/maintenance, release readiness checks, incident triage and root-cause acceleration), while defining guardrails for validation, security, resiliency, and reuse across teams.
• 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 at scale.
• Leverage Databricks for data processing, model training, and deployment.
• Utilize Gen AI tools and frameworks to enhance model performance and capabilities.
• Implement best practices for LLM Ops to ensure efficient model lifecycle management.
• Lead the production of Gen AI use cases, ensuring robust and scalable solutions.
• Work closely with data scientists, engineers, and product teams to deliver AI-driven solutions.
• Mentor and guide junior team members, fostering a culture of innovation and excellence.
• Monitor the performance of AI/ML models and platforms, identifying areas for improvement.
• Implement optimization techniques to enhance model accuracy, efficiency, and scalability.

Required qualifications, capabilities and skills:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Minimum 8+ years of experience in AI/ML engineering, with a focus on AWS, Databricks, and Gen AI.
• Strong understanding of AI/ML algorithms, model serving, and fine-tuning techniques.
• Proven experience in LLM Ops and the production of Gen AI use cases.
• Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.
• Strong communication and leadership skills, with the ability to influence and drive change.
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Expert in one or more programming language(s)
• Demonstrated experience designing and leading adoption of agentic AI-enabled development practices (using enterprise-authorized tools within the work environment) across teams, including setting standards for human-in-the-loop validation, auditability/traceability of changes, and secure handling of sensitive data.
• Strong understanding of responsible AI use and control expectations in engineering workflows, including security/resiliency implications, data sensitivity, and risk-based governance; ability to influence senior technical leaders on safe scaling patterns and reuse.
• Experience applying expertise and new methods to determine solutions for complex technology problems in one or more technical disciplines
• Ability to present and effectively communicate with Senior Leaders and Executives
• Understanding of the business
• Practical cloud native experience

Preferred qualifications, capabilities and skills:

• Experience with other cloud platforms and AI/ML tools.
• Familiarity with data engineering and data science workflows.
• Knowledge of regulatory and compliance requirements related to AI/ML solutions