Artificial Intelligence Jobs in Saint Paul, MN

Leads product vision, roadmap, backlog management, prioritization, and Agile delivery for AI-enabled workflow transformation in Global Corporate Trust. Identifies process improvement opportunities, translates stakeholder needs into scalable solutions, coordinates testing and delivery, evaluates emerging AI capabilities, and drives change management, readiness, and adoption. Partners with business and technology teams to deliver governed AI solutions that improve productivity, decision-making, operational efficiency, and stakeholder experiences.

Own the vision, strategy, roadmap, and outcomes for Augeo’s Incentives product domain. Partner with AI, data science, engineering, and business teams to build ML-driven incentive decisioning, experimentation, personalization, catalog configuration, and automation capabilities. Translate incentive economics and stakeholder needs into prioritized requirements, measure engagement and ROI, ensure privacy and governance compliance, and lead cross-functional planning and delivery.

Leads business process transformation for AI solutions across sales, service, customer, and operational workflows. Defines current and future-state processes, prioritizes AI use cases, translates business needs into requirements, establishes operating models and KPIs, and drives adoption and value realization. Partners with executives, product, engineering, UX, data science, and business teams to align strategy, governance, solution delivery, organizational readiness, and measurable business outcomes.

Design, deploy, and optimize autonomous multi-agent AI architectures for semiconductor IP block development and support workflows. Integrate LLM orchestration and Model Context Protocol systems with enterprise verification frameworks to improve efficiency, quality, and automation across hardware engineering processes.

Leads the global custody operations function, overseeing securities settlement, corporate actions, asset servicing, reconciliations, sub-custodian networks, risk controls, regulatory compliance, resilience, client escalations, budgets, and workforce strategy. Drives transformation from batch processing to real-time exception management using automation, AI, cloud, and ISO 20022. Builds leadership depth, manages vendors and market relationships, and ensures efficient, accurate, compliant servicing of client assets across global markets.

Leads Ecolab’s Digital Audit function and third line of defense for IT and digital risk. Owns the audit strategy, multi-year roadmap, annual audit plan, advisory work, co-source relationships, and digital control improvements. Oversees SOX ITGC testing, audit analytics and GRC enhancements, executive reporting, and audit committee communications. Builds and develops a high-performing team while advising Digital, Finance, Enterprise AI, and business leaders on technology risks, controls, and emerging issues.

Build and operationalize data pipelines and cloud data solutions using AWS, Databricks, dbt, SQL, and PySpark. Responsibilities include data transformation, cleansing, governance, security, quality, testing, defect resolution, source analysis, and supporting AI, machine learning, and business intelligence. The role collaborates with business partners and cross-functional teams to design solutions, deliver data products, and improve analytics capabilities.

Leads enterprise AI architecture strategy, standards, governance, and reference architectures. Designs scalable production AI, generative AI, agentic AI, RAG, LLM, and MLOps solutions while guiding cloud, platform, security, compliance, cost, and integration decisions. Advises technology and business leaders, aligns AI capabilities with business goals, promotes responsible AI practices, tracks emerging technologies, and mentors architecture teams.

Leads enterprise AI governance across the full AI lifecycle, including classification, risk assessment, inventory management, approval workflows, committee facilitation, and audit readiness. Partners with technology, security, data governance, model risk, third-party risk, and compliance teams to ensure responsible AI adoption aligned with regulatory expectations. Develops assessment methodologies, tracks conditional approvals, maintains AI governance documentation, and supports regulatory examinations.

Tenure-track Assistant Professor of Mathematics responsible for teaching introductory and upper-level undergraduate courses, advising students, conducting an active research program, mentoring undergraduate research, and contributing departmental service. Preferred research areas include applied mathematics, machine learning, artificial intelligence, optimization, operations research, and numerical methods. The position requires excellence in teaching, potential for sustained research, and commitment to an inclusive academic environment.

Designs and guides enterprise AI solution architectures across corporate technology domains. Defines target-state architectures, technology roadmaps, reusable AI patterns, integration frameworks, and governance standards. Partners with enterprise architects and development teams to modernize systems, reduce technical debt, and enable scalable AI adoption. The role requires hands-on experience with cloud-native technologies, APIs, event-driven messaging, LLM-enabled applications, and modern architecture practices, with insurance or corporate capability experience preferred.

Identify and evaluate enterprise AI and transformation opportunities, quantify business value, and translate business needs into responsible AI use cases. Develop proofs of concept, knowledge bases, and conversational AI agents; facilitate discovery workshops; collaborate with leadership, Technology, Risk, Compliance, and Operations; present recommendations; support adoption through training and communication; and contribute to AI governance, playbooks, and capability building.

Lead design, development, and production deployment of enterprise AI agents and LLM-powered tooling to automate engineering workflows. Define technical vision, set standards, mentor engineers, partner with stakeholders, and ensure reliability, observability, and scalability of agentic systems.

Design, build, and deliver enterprise AI solutions using LLMs, cloud platforms, and container orchestration. Own end-to-end delivery, partner with stakeholders, coach junior engineers, and produce production-ready integrations, prototypes, and automations.

Design, implement, test, and maintain cloud-native software solutions. Troubleshoot complex defects, build APIs and integrations, enable AI/LLM capabilities, mentor junior engineers, contribute to CI/CD and observability, and collaborate with cross-functional teams to deliver reliable systems.