Senior AI Engineer; Hybrid

Position: Senior AI Engineer (Hybrid)
## Senior AI Engineer (Hybrid)
Apply locations:
Saint Paul, MN Campus time type:
Full time posted on:
Posted 2 Days Agojob requisition :
R-010649
* Securian Financial Group’s internal position title is Engineering Consultant.
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* Position Summary:

** The Senior AI Engineer is a key member of Securian Financials' Enterprise Data and Analytics team, working closely with Data Science, Data Engineering, and the Artificial Intelligence Center of Excellence (AI CoE). These teams serve as the enterprise’s internal experts on how to apply Data and Analytics and AI at scale turning strategy into enablement, consultation, and delivery support across the business.

In this role, you will shape, evaluate, and advance the platforms, tools, architectures, and foundational technologies required to deliver AI at enterprise scale especially. You will lead experimentation and proof-of-concept efforts, assess emerging AI technologies, inform platform selection decisions, and guide the creation and adoption of standards for reusable and extensible AI solution patterns. You’ll act as a highly collaborative internal consultant partnering with teams across the company to ensure AI solutions are scalable, sustainable, secure, and aligned with enterprise strategy.

You will also serve as a two-way conduit with analogous Platform Engineering teams across the enterprise, ensuring their perspectives influence CoE strategy and that they are equipped to adopt CoE-developed standards, technologies, and ways of working. We are seeking highly curious, collaborative, and self-organized associates who thrive in ambiguity, are passionate about emerging technologies, and enjoy driving clarity in a rapidly evolving AI landscape.

Your work ensures associates across Securian have the right platforms and guardrails to develop safely and efficiently.
** Responsibilities include but not limited to:
*** Champion the selection, evaluation, and lifecycle management of AI platforms, frameworks, and tools used across the enterprise, drawing from deep technical expertise and market awareness.
* Serve as an internal SME especially during project discovery phases on enterprise AI platform architecture including model lifecycle tooling, containerization, orchestration, vector databases, prompt management, RAG frameworks, and model hosting options.
* Rapidly experiment with new AI services, foundation models, and developer tooling to assess maturity, extensibility, and alignment with long-term enterprise AI strategy.
* Partner with AI delivery teams to guide solution design and ensure the reuse of approved enterprise AI patterns before pursuing net-new platform development or procurement.
* Document, maintain, and coach teams on AI platform standards, best practices, and reference architectures for scalable and responsible AI.
* Work closely with Enterprise Technology to ensure AI platforms are secure, compliant, cost-efficient, and operationally resilient.
* Act as a bridge between the AI CoE and analogous technical platform teams elsewhere in the organization ensuring two-way knowledge flow, alignment on technology directions, and adoption of shared best practices.
* Consult with product owners, data scientists, and engineers to identify platform gaps and implement enhancements that improve efficiency and developer experience.
* Support the creation of platform-level safeguards and governance controls to ensure responsible, sustainable, and secure AI use across the enterprise.
* Contribute to the development of enterprise guidelines that ensure AI solutions are adaptable to rapidly evolving model capabilities and ecosystem changes.
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* Qualifications:

*** Strong technical experience across AI, ML, and cloud platform engineering particularly in researching, implementing, and onboarding new technologies and tooling.
* Hands-on expertise with cloud environments (AWS strongly preferred), including services relevant to AI/ML development, deployment, and data processing.
* Experience deploying, integrating, or supporting AI/ML systems in production, including MLOps pipelines, model hosting, and monitoring solutions.
* Demonstrated ability to conduct proof-of-concept work, evaluate emerging technologies, and translate findings into actionable recommendations.
* Strong understanding of modern AI stacks including APIs, foundation models, vector databases, orchestration tools, and retrieval-augmented generation (RAG) patterns.
* Ability to build strong partnerships, and collaborate with both technical and non-technical stakeholders.
* Strong curiosity, analytical skills, and comfort working in ambiguity to define and evaluate options.
* Ability to clearly communicate complex technical concepts and guide teams toward shared standards and patterns.
* Experience working in or with Enterprise Architecture, platform engineering, or MLOps functions.
* Familiarity with AI-specific security, governance, and responsible AI considerations.
* Background in financial services or other regulated…