Lead Architect; Data and Artificial Intelligence - Remote

Position: Lead Architect (Data and Artificial Intelligence) - Remote

Mutual of Omaha is seeking a visionary Data and AI Architect to lead the design and evolution of intelligent data-driven platforms across our Workplace Solutions division. This position will champion strategic initiatives leveraging data, analytics, and artificial intelligence to enhance customer experiences, optimize operations, and drive business value through scalable and ethical technology solutions.

This role is essential in shaping our data architecture, artificial intelligence strategy, and governance models, enabling intelligent automation, machine learning operations (MLOps), and integrated insights. The ideal candidate brings deep technical expertise and an innovative mindset to accelerate our journey toward becoming a data-powered organization.

As a Lead Architect within Workplace Solutions Integration ART, you will work closely with business and technology partners to deliver modern, secure, and adaptive data ecosystems and AI solutions. You will contribute to Mutual of Omaha’s transformation by establishing a future-ready data foundation and operationalizing AI to unlock actionable intelligence.

WHAT WE CAN OFFER YOU:

• Estimated Salary: $160,000 - $185,000, plus annual bonus opportunity.
• 401(k) plan with a 2% company contribution and 6% company match.
• Work-life balance with vacation, personal time and paid holidays. See our benefits and perks page for details.
• Applicants for this position must not now, nor at any point in the future, require sponsorship for employment.

WHAT YOU’LL DO:

• Data and AI Architecture Leadership: Design and implement advanced data platforms and AI architecture, enabling enterprise-scale analytics, machine learning, and intelligent automation across the division.
• Strategy & Planning: Collaborate with enterprise architects and business stakeholders to define a vision and roadmap for data modernization, MLOps, and AI governance aligned to strategic outcomes.
• AI Innovation & Prototyping: Lead the development of AI models, POCs, and pipelines using cutting-edge technologies. Explore “what-if” scenarios, whiteboarding, and design sprints to evaluate new opportunities and validate business impact.
• Governance & Ethics: Establish and uphold standards for data quality, stewardship, ethical AI practices, and secure model deployment while promoting regulatory compliance and trust.
• Mentorship & Enablement: Coach engineers and analysts in data modeling, feature engineering, and ML development. Promote knowledge sharing and establish best practices across data science and data engineering teams.
• Collaboration & Integration: Integrate data solutions with microservices, event-based architectures, and external business partners, ensuring scalability, observability, and operational readiness.

WHAT YOU’LL BRING:

• 5+ years of experience in leading data and AI architecture initiatives, including cloud-native data platforms, machine learning lifecycle management, and enterprise data integration.
• Expertise in distributed data systems, data warehouse, data lakehouse architecture, and model operationalization frameworks such as MLflow, Sagemaker, or similar.
• Proficiency in Python, SQL, Snowflake and Mongo

DB and cloud technologies (AWS preferred), with experience deploying ML models using containers, APIs, or serverless frameworks. Proficiency in logical and physical data modeling, Multidimensional modeling, normalization and denormalization techniques. Experience in building data systems in Micro service environment that provide access to data for operational and Analytical needs (BI/ML/AI).

• Experience translating business strategies into data and AI solutions with measurable outcomes. Proficiency in design and developing of ETL/ELT methodologies from source to target supporting data processing and transformations to deliver data driven business insights and decisions.
• Strong understanding of AI/ML ethics, explainability, governance, and responsible AI principles. Familiarity with data observability tools, CI/CD for ML, and lineage/trust frameworks.
• Comfortable working in agile environments and guiding architecture for Agile Release Trains (ART). Excellent communication, stakeholder engagement, and…