AI Engineering Manager

Thrivent•Minneapolis, MN

About The Position

Thrivent is seeking an experienced AI Engineering Manager to lead a high-performing team building scalable, secure, and compliant production AI systems. You will combine deep technical leadership with strategic oversight to drive agentic AI, LLM/RAG, and classical ML initiatives from ideation through production and operations across AWS and Azure. Success looks like resilient platforms, measurable business outcomes, and a healthy engineering culture. You’ll do this by: Leading and mentoring a team to deliver solutions spanning model development, agentic system design, and AI integration—ensuring observability, security, performance, and cost efficiency. Providing expertise in AI governance & Responsible AI aligned to financial-services expectations (e.g., NIST AI RMF, model risk management, GLBA privacy). Establishing operating policies, engineering standards, and SDLC/ML lifecycle practices that scale across teams. Translating company-wide objectives into budgets, roadmaps, OKRs, and measurable outcomes. Partnering with senior business and technology stakeholders to shape strategy, unblock delivery, and ensure compliance. Leading briefings and technical reviews that support IT objectives and executive decision-making.

Requirements

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 relationship and demand management.

Nice To Haves

Financial Services industry experience
Experience in IT planning and business relationship management
Experience working in a matrix management organization
Experience with product development and management

Responsibilities

Designing Solutions Guide end-to-end architecture for AI systems (data → features → models → serving → monitoring), spanning AWS & Azure ; review ADRs and ensure threat modeling , data lineage, and cost/perf trade-offs are explicit.
Land decisions on RAG patterns, agent orchestration, vector indexing, prompt management, evaluation , and human-in-the-loop controls for regulated use cases.
Sponsor reference architectures (Bedrock vs. SageMaker vs. EKS; Azure OpenAI vs. Azure ML vs. K8) and promote reuse via templates and golden paths.
Developing Software Maintain hands-on credibility: read code , give architectural/code reviews , and insist on testing, type safety, CI/CD, IaC , and SRE hygiene (SLOs/error budgets).
Uphold secure coding and data protection (PII handling, tokenization, KMS/Key Vault, private networking).
Learning & Applying New Techniques Create space for tech spikes , brown-bags, and internal demos; track advances in LLM inference (vLLM/TGI/ONNX/TensorRT) , guardrails , evals, and privacy-preserving ML .
Anticipate trends (context-window management, retrieval quality, tool-use/agents, model distillation/quantization) and adapt roadmaps.
Collaborating (Team, Cross-Team, Org) Strengthen agile practices (scrum/kanban), partner with Product on outcomes & metrics , and remove systemic blockers.
Broker cross-product solutions (common feature store , prompt/eval service , model registry , shared vector search ).
Align the team to company priorities and risk posture; ensure auditability and runbooks.
Setting Product/Platform Technology Strategy Co-create vision, strategy, and roadmaps for AI platform & products; influence backlog with business value cases and risk/cost transparency.
Empower the team to choose fit-for-purpose tools within guardrails; rationalize where to buy vs. build .
Defining Engineering Standards/Patterns Codify ML/LLM golden paths (templates for RAG, batch/online inference, streaming features).
Champion observability-by-default (tracing, prompt logs, retrieval quality metrics, safety incident workflow).
Contribute to enterprise frameworks (data contracts, model governance, rollout patterns).
DevOps / MLOps / LLMOps Own the ML/LLM lifecycle : data quality → experiment tracking → model registry → gated promotions → canary/shadow → monitoring & drift response.
Serve as escalation for production incidents ; drive post-mortems , defect SLAs, and continuous improvement .
Continuously evaluate latency, reliability, accuracy, safety, and cost .
Selecting & Managing Technology Vendors Define selection criteria ; lead RFPs/POCs ; manage vendor performance, SOWs, Be an advocate to the team to define criteria’s for selecting the right platform/technology
Guides the team to build consensus on an approach and driving a build vs buy decision with the team. In a buy decision, works with the team to decide on criteria and vendor selection.
Execute or manage the overall technology solutions, platforms for the product groups and associated vendor relationships.
Coaching Engineers o Holding regular 1:1s with team members and team meeting,
Provides constructive feedback, guidance and coaching to help engineers grow their skills and experience.
Provides career planning advice to engineers and creates development plans to help them achieve their career goals which leverages their skills and capabilities and provides them with learning opportunities.
Recruiting/building talent o Leads the process of selecting and engaging the right consulting partners
Planning in advance for future people needs for the product groups, collaborate with the other teams on the recruitment process
Recruits, develops, and sustains a high-performing team while promoting a culture of shared accountability, operational excellence, and partnership across the organization.
Models Thrivent’s leadership competencies – courage, collaboration, and commitment by demonstrating resiliency, working together to make the best decisions, and holding yourself and others accountable.
Supports and/or develops an environment in which Thrivent employees and colleagues are focused on continuous improvement, exceptional employee engagement, and an unwavering commitment to our clients.
Shapes and/or supports a culture that represents the Thrivent purpose, promise and values, ensuring that Thrivent’s trust and reputation remain strong with its clients.
Manage a team of direct and indirect staff

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, and other employee benefits
Eligibility for receipt of these benefits is subject to the applicable plan/policy documents.
Thrivent’s plans/policies are subject to change at any time at Thrivent’s discretion.