[Remote] Mgr, Engineering

Note: The job is a remote job and is open to candidates in USA. Thrivent is seeking an experienced AI Engineering Manager to lead the team responsible for building their enterprise AI/ML platform. This role involves guiding the development of scalable and efficient AI solutions while fostering a strong engineering culture and ensuring alignment with business goals.

Responsibilities

• 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
• 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
• 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
• 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
• 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

Skills

• 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
• 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

Benefits

• Various bonuses (including, for example, annual or long-term incentives)
• Medical, dental, and vision insurance
• Health savings account
• Flexible spending account
• 401k
• Pension
• Life and accidental death and dismemberment insurance
• Disability insurance
• Supplemental protection insurance
• 20 days of Paid Time Off each year
• Sick and Safe Time
• 10 paid company holidays
• Volunteer Time Off
• Paid parental leave
• EAP
• Well-being benefits
• Other employee benefits

Company Overview

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