Thrivent is seeking an experienced AI Engineering Manager to help lead the team that builds Thrivent’s enterprise AI/ML platform — the capabilities that product delivery teams across the organization use to develop, deploy, and operate AI solutions spanning classical machine learning, LLM/RAG applications, and agentic systems. The platform is built on Databricks for machine learning and data science and on AWS for production serving, with Amazon Bedrock and SageMaker powering LLM workloads. The team operates in a product operating model: the platform is the product, delivery teams are its customers, and the team partners with Product Management to drive a capability roadmap measured by adoption and business outcomes.
DUTIES & RESPONSIBILITIES:
Platform & Solution Leadership
Review AI/ML and platform solution designs — classical ML, LLM/RAG, and agentic systems — and provide guidance on scalability, security, cost, and compliance across Databricks and AWS
Shape reference architectures and reusable, paved-road patterns (training pipelines, deployment templates, retrieval services, repository bootstrapping) that make the right way the easy way for delivery teams
Maintain strong technical fluency in AI/ML systems; able to read code and guide best practices across model integration, APIs, and platform services
Apply strong problem-solving and analytical skills to guide teams through complex AI/ML and platform challenges
Product Operating Model & Customer Enablement
Partner closely with Product Management to define strategies, operating plans, roadmaps, targets, and measures for the platform capabilities the team owns
Treat the platform as a product: understand the needs of Thrivent’s delivery teams, drive adoption through enablement, documentation, and support, and measure success by customer outcomes
Help set the product and platform technology vision in partnership with AI engineering leadership; represent the business value of platform investments and influence prioritization in the roadmap
Support the team’s agile practices; engage in sprint demos and understand both the outcomes sought and the technology delivered
Build strong working relationships with peers across teams; proactively identify cross-team challenges and empower teams to solve them collaboratively
Engineering Standards & Operational Excellence
Champion engineering excellence across AI/ML and platform development, including code review, testing, CI/CD, MLOps, observability, and reliability practices
Build evaluation and observability into the platform as first-class capabilities for LLM and agentic systems, including automated evaluation, drift monitoring, and tracing
Partner with model risk, security, and compliance functions to automate governance: risk-tier classification, policy-gated promotion, and audit-ready evidence
Own the operational health of the team’s services: monitoring and alerting, serving as an escalation point for production incidents, and prioritizing work to maintain and continuously improve product health
Technology Strategy & Vendor Selection
Stay ahead of trends in AI/ML, platform engineering, and cloud (AWS), assess their impact on business capabilities and strategy, and create space for teams to experiment with and adopt emerging techniques
Guide build-versus-buy decisions and tool selection for the team’s capability areas; define selection criteria with the team and manage associated technology vendor and consulting relationships
People Leadership
Hold regular 1:1s and team meetings; provide constructive feedback, guidance, and coaching to help engineers grow their skills and experience
Provide career planning advice and create development plans that leverage engineers’ skills and capabilities and provide learning opportunities
Recruit, develop, and sustain a high-performing team while promoting a culture of shared accountability, operational excellence, and partnership across the organization; plan ahead for future people needs, including selecting and engaging consulting partners
Create a positive team environment where individuals have psychological safety and work collaboratively while understanding, respecting, challenging, and appreciating each other’s ideas
Model Thrivent’s leadership competencies of courage, collaboration, and commitment, while supporting a culture that represents the Thrivent purpose, promise, and values, ensuring Thrivent’s trust and reputation remain strong with its clients
Manage a team of direct and indirect staff
QUALIFICATIONS & SKILLS:
Required:
Bachelor’s degree in Computer Science or other technical field or equivalent work experience
8+ years of progressively responsible positions in Information Technology including 5+ years’ experience in IT discipline, e.g., customer relationship management, portfolio strategy and roadmap development.
3+ years of leadership experience in all aspects of a specific IT discipline, e.g. IT/LOB customer relationship management, portfolio strategy and/or demand management.
3+ years’ management/supervisory experience in specific IT functional area discipline, e.g. applications development or equivalent skills leading major technical projects with accountability for enforcing talent management needs and performance standards.
Demonstrated leadership and experience managing multidiscipline, high-performance work teams.
Strong competency in project management and execution of multiple or large projects.
Experience working with customers to develop solutions to complex business problems.
Proven ability to communicate effectively with internal/external stakeholders to support business initiatives.
Proven ability to function in an environment which requires flexibility, good judgment, and intelligent decision making, often based on limited information and/or extreme conditions.
Ability to formulate, implement and evaluate plans, programs and procedures applicable to customer relationships and demand management.
Preferred:
Hands-on experience building or operating production ML or LLM systems, with working fluency in modern AI patterns — RAG, agentic systems, and model lifecycle/MLOps — sufficient to credibly review designs and code
Experience with the platform’s core stack: Databricks (including MLflow and Unity Catalog) and AWS (including Amazon Bedrock and SageMaker), along with modern CI/CD and infrastructure-as-code tooling
Experience leading internal platform, ML platform, or developer-experience teams, including platform-as-a-product practices and adoption/outcome metrics
Familiarity with evaluation and observability for LLM and agentic systems (automated evaluation, hallucination detection, drift monitoring, tracing)
Familiarity with agentic AI patterns such as Model Context Protocol (MCP), multi-agent orchestration, and human-in-the-loop design
Experience with AI governance, model risk management, or responsible AI practices in financial services or another regulated industry
Financial Services industry experience
Pay Transparency
Thrivent provides Equal Employment Opportunity (EEO) without regard to race, religion, color, sex, gender identity, sexual orientation, pregnancy, national origin, age, disability, marital status, citizenship status, military or veteran status, genetic information, or any other status protected by applicable local, state, or federal law. This policy applies to all employees and job applicants.
Thrivent is committed to providing reasonable accommodation to individuals with disabilities. If you need a reasonable accommodation, please let us know by sending an email to human.resources@thrivent.com or call 800-847-4836 and request Human Resources.
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