Director of Software Engineering, MLOps & ML Governance

Our Vision

Empower's vision centers on empowering financial lives by first empowering its people. We champion a flexible work environment, fluid career paths, and celebrate internal mobility. We understand the importance of purpose, well-being, and work-life balance, fostering an inclusive environment where associates actively volunteer for causes they care about. Chart your own path and grow your career while helping more customers achieve financial freedom with Empower.

Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment visa at this time, including CPT/OPT.

About the Role: Director of Software Engineering, MLOps & ML Governance

The Director of Software Engineering, MLOps & ML Governance is critical to the success and growth of a core technical unit within Empower. This leadership role drives innovation and collaborates extensively with senior leaders across product, engineering, data science, risk, and compliance to advance the organization's strategic business initiatives. A primary focus will be leading the MLOps function, ensuring the development of scalable, secure, and compliant machine learning solutions that adhere to enterprise governance and risk frameworks.

What You Will Do

• Lead the execution of deliverables with risk and engineering teams, ensuring projects meet deadlines, requirements, and budgets.
• Be accountable for team performance within assigned software engineering and MLOps initiatives.
• Serve as a subject matter expert on multiplatform applications and ML infrastructure, guiding strategic decisions.
• Direct the system development lifecycle for proprietary and purchased software, including design, coding, testing, documentation, maintenance, and support.
• Lead the design, implementation, and scaling of enterprise MLOps platforms, encompassing CI/CD pipelines for ML, model versioning, automated testing, monitoring, and lifecycle management.
• Establish best practices for model deployment, observability, performance monitoring, drift detection, and retraining strategies.
• Partner with Data Science, Risk, Compliance, Legal, and Information Security teams to ensure ML systems meet all regulatory, governance, and risk management requirements.
• Implement and oversee ML governance frameworks, including model documentation, validation, explainability, auditability, fairness/bias monitoring, and model risk management controls.
• Ensure adherence to enterprise data governance, privacy, and AI risk policies, including responsible AI standards.
• Recommend innovations and improvements to policies and procedures, making decisions that impact mid- to long-term operational results.
• Develop long- and short-term business and technology strategies aligned with AI/ML roadmaps.
• Manage operating costs and budgets, including infrastructure investments for ML platforms.
• Make decisions on pay, performance, appraisals, schedules, discipline, and hiring.
• Build and lead a high-performing MLOps and engineering organization, establishing clear career paths and leadership development.

What You Will Bring

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field; or equivalent professional experience.
• 10+ years of experience in software engineering, with a focus on distributed or cloud-based systems.
• 4+ years of successful team management experience (including managers), demonstrating an ability to develop, motivate, and direct leaders and technical contributors.
• Proven experience leading or building an MLOps function or production-grade ML platforms within an enterprise setting.
• Strong understanding of ML lifecycle management, including training, validation, deployment, monitoring, and governance.
• Experience implementing ML governance and model risk management frameworks (e.g., documentation, validation controls, bias/fairness testing, explainability, audit readiness).
• Familiarity with regulatory expectations for AI/ML in highly regulated industries (e.g., financial services).
• Proficiency with cloud platforms (AWS, Azure, GCP), containerization (Docker/Kubernetes), CI/CD pipelines, and infrastructure-as-code.
• Strong understanding of data governance, privacy, security, and compliance related to AI/ML systems.
• Ability to manage a leadership pipeline by mentoring subordinate managers and nurturing senior technical talent.
• Excellent executive communication skills, translating complex ML and risk topics into business-aligned decisions.

What We Offer You

Empower provides diverse and inclusive benefits aimed at supporting a healthy, balanced life and optimal work performance. Benefits include:

• Medical, dental, vision, and life insurance.
• Retirement savings: 401(k) plan with generous company matching (up to 6%), financial advisory services, potential discretionary contributions, and a broad investment lineup.
• Tuition reimbursement up to $5,250/year.
• Business-casual environment with jeans option.
• Generous paid time off, including a PTO program, ten paid company holidays, and three floating holidays.
• Paid volunteer time: 16 hours per calendar year.
• Leave of absence programs: paid parental leave, short- and long-term disability, and FMLA.
• Business Resource Groups (BRGs) fostering inclusion and collaboration.

The salary range above shows the typical minimum to maximum base salary range for this position in the location listed. Non-sales positions have the opportunity to participate in a bonus program. Sales positions are eligible for sales incentives, and in some instances a bonus plan, whereby total compensation may far exceed base salary depending on individual performance. Actual compensation offered may vary from posted hiring range based upon geographic location, work experience, education, licensure requirements and/or skill level and will be finalized at the time of offer.

Empower is an equal opportunity employer with a commitment to diversity. All individuals, regardless of personal characteristics, are encouraged to apply. All qualified applicants will receive consideration for employment without regard to age (40 and over), race, color, national origin, ancestry, sex, sexual orientation, gender, gender identity, gender expression, marital status, pregnancy, religion, physical or mental disability, military or veteran status, genetic information, or any other status protected by applicable state or local law. We are a drug-free workplace.

For remote and hybrid positions you will be required to provide reliable high-speed internet with a wired connection as well as a place in your home to work with limited disruption. You must have reliable connectivity from an internet service provider that is fiber, cable or DSL internet. Other necessary computer equipment, will be provided. You may be required to work in the office if you do not have an adequate home work environment and the required internet connection.

Key skills/competency

• MLOps
• Machine Learning Governance
• Software Engineering Leadership
• Cloud Platforms (AWS, Azure, GCP)
• CI/CD Pipelines
• Model Risk Management
• Distributed Systems
• Data Governance
• Containerization (Docker/Kubernetes)
• AI/ML Strategy