As a Sr Engineer II (Team Leader, Model Operations & Enablement), you will lead the team that builds and operates Principal's Enterprise AI pipeline platforms — the platform our builders rely on to deploy, monitor, and maintain AI models in production. You will work closely with data science, engineering, and business stakeholders across our company to standardize how models move from idea to production and stay healthy once they're there.

Key Responsibilities:

• Lead the MOE team and grow its capabilities to own and design all layers of the model operations stack. Model training (AWS SageMaker, XGBoost, Scikit-Learn, PyTorch), CI/CD deployment, real-time and batch inference serving, and production monitoring
• Own and continually reduce the complexity of the enterprise AI pipeline, including AWS (Glue, S3, SageMaker, IAM), the Snowflake-based Enterprise Data Foundation (EDF), and model registry
• Set short- to medium-term strategic direction for the MOE platform (6–12 months out), including expanding automated model monitoring and drift detection, and extending LLMOps coverage (performance stability, latency, uptime, logging, security, explainability) as generative and agentic use cases come online
• Run recurring intake consultations and "office hours" with data science partners to scope new products and move the model backlog (value/expected-value models, retention and cross-sell likelihood models, claims monitoring, customer lifetime value, and similar) from consultation through operationalization
• Facilitate cross-team work between MOE and data science/analytics engineering partners, including migrating legacy models off ad hoc pipelines and onto the enterprise MLOps pipeline
• Own the change-management rigor (risk/impact analysis, migration plans) required to ship safely in a regulated insurance and financial services environment, including privacy impact assessments where third-party data is involved
• Build technical depth and a leadership bench on the team: give each team member the opportunity to lead or co-lead an ML project over the year, and foster a culture of accountability, coaching, and career development
• Create and deliver training on the MLOps pipeline, present MLOps progress and thought leadership at least quarterly, and measure pipeline usability directly with end users
• Provide technical guidance and mentorship

Operating at the intersection of financial services and technology, Principal builds financial tools that help our customers live better lives. We take pride in being a purpose-led firm, motivated by our mission to make financial security accessible to all. Our mission, integrity, and customer focus have made us a trusted leader for more than 140 years.

As Principal continues to modernize its systems, this role will offer you an exciting opportunity to build solutions that will directly impact our long-term strategy and tech stack, all while ensuring that our products are robust, scalable, and secure!

We are looking for someone with:

• Associate or bachelor's degree (preference in a computer science, technology, engineering, or math-related field) and 8+ years' work experience or equivalent experience
• 5+ years of experience working with AWS is required (Glue, S3, SageMaker, IAM), Snowflake, feature store and model registry concepts, and ML frameworks (XGBoost, Scikit-Learn, PyTorch).
• Formal Leadership experience is required. (leading or managing a technical team, including coaching and career development)
• Proven experience as an IT professional, with demonstrated experience in MLOps, ML infrastructure, or similar model-operations work
• Experience leading or managing a technical team, including coaching and career development
• Experience standing up or operating model monitoring and drift detection in production
• Familiarity with agile methodologies

Skills That Will Help You Stand Out

• Solid understanding of CI/CD deployment patterns for real-time and batch inference
• AWS Certified AI Practitioner or higher-level AWS certification
• Experience with LLMOps practices (bias/toxicity drift, latency, explainability monitoring) for generative or agentic model use cases
• Experience running intake/consultation processes to scope ML products with business stakeholders
• Strong presentation skills and a track record of communicating technical work to non-technical audiences
• Basic knowledge of insurance and financial services products (e.g., retirement/income solutions, group benefits, individual life)

Job level

We’ll consider talent at the next level with the right experiences and skills.

Work Environments

This role offers in-office, hybrid (blending at least three office days in a typical workweek). You’ll work with your leader to figure out which option may align best based on several factors.

At this time, we're not considering candidates that need any type of immigration sponsorship (additional work authorization or permanent work authorization) now or in the future to work in the United States. This includes, but IS NOT LIMITED TO: F1-OPT, F1-CPT, H-1B, TN, L-1, J-1, etc. For additional information around work authorization needs please use the following links.

Investment Code of Ethics

For Principal Global Investors positions, you’ll need to follow an Investment Code of Ethics related to personal and business conduct as well as personal trading activities for you and members of your household. These same requirements may also apply to other positions across the organization.

While our expertise spans the globe, we're bound by one common purpose: to foster a world where financial security is accessible to all. And our success depends on the unique experiences, backgrounds, and talents of our employees – individually and all of us together. Explore our core values, benefits and why we’re an exceptional place to grow your career.