Full-Time

Vice President – AI Solutions Architecture

 RGA Reinsurance Company

RGA Reinsurance Company

Compensation Overview

$180.2k - $268.4k/yr

+ Bonus + Equity Incentive Plan

Chesterfield, MO, USA + 1 more

More locations: United States

In Person

Category
Software Engineering (1)
Required Skills
Python
SQL
MLflow
RAG
Microservices
AWS
Data Governance
Databricks
Snowflake
Requirements
  • Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Science, or a related technical field.
  • Experience: 15+ years of progressive experience in solutions architecture, enterprise architecture, or technical leadership, with at least 5 years designing AI/ML systems, data platforms, or cloud-native applications at scale.
  • Cloud & Data Platform Expertise: Deep hands-on experience architecting solutions on Databricks (Unity Catalog, Delta Lake, MLflow, Model Serving, Workflows) and AWS (SageMaker, Lambda, Step Functions, S3, ECS/EKS, API Gateway, Bedrock). Proficiency with Python and SQL.
  • AI/ML Systems Design: Expert understanding of end-to-end machine learning system architecture, including training pipelines, feature stores, model registries, real-time and batch inference, vector databases, retrieval-augmented generation (RAG), and agentic AI orchestration patterns.
  • Solution Design & Documentation: Proven ability to author comprehensive solution design documents that clearly communicate data flows, system topology, API contracts, infrastructure requirements, scaling strategies, and operational runbooks to diverse audiences.
  • Cost Modeling & FinOps: Experience building and maintaining solution-level cost models (cost per inference, total cost of ownership) and driving optimization across cloud compute, storage, and third-party AI services.
  • Technical Leadership & Influence: Demonstrated ability to lead architecture reviews, mentor engineers and data scientists, set technical direction, and drive alignment across cross-functional teams without direct authority.
  • Communication & Executive Presence: Exceptional ability to distill complex technical architectures into clear documentation, diagrams, and presentations tailored for technical peers, business stakeholders, and senior leadership.
  • Integration & API Design: Strong expertise in designing scalable APIs, event-driven architectures, microservices, and enterprise integration patterns for production AI systems.
  • Stakeholder Partnership: Proven track record of partnering with product management, data science, engineering, and business teams to translate strategic priorities into well-architected technical solutions.
  • Analytical & Strategic Thinking: Strong ability to evaluate architectural trade-offs, assess technical risk, model capacity scenarios, and make sound design decisions that balance innovation with operational reliability.
Responsibilities
  • Solution Design & Technical Architecture: Lead the creation of end-to-end solution architecture for AI and data initiatives, defining data pipelines, model serving infrastructure, integration points, API integration, compute sizing, and scaling strategies across Databricks, Snowflake and AWS.
  • Architecture Standards & Reusable Patterns: Establish and evolve reusable architecture patterns, reference architectures, and design templates that ensure consistency and accelerate delivery across the AI and data solutions portfolio, leveraging Databricks Unity Catalog, Delta Lake, Snowflake, and AWS-native services.
  • Cost Optimization & FinOps: Own solution-level cost modeling including cost-per-inference, cost-per-user, and total cost of ownership analyses; identify optimization opportunities across Databricks compute, AWS infrastructure, and third-party services; and contribute to broader technology spend governance.
  • Cross-Functional Architecture Partnership: Serve as the primary technical solution design partner to product management, data science, data solutions, and engineering teams—translating business requirements and product specifications into actionable, well-documented technical designs.
  • Security, Compliance & Data Governance: Embed enterprise security standards, data governance policies, and applicable regulatory requirements into every solution architecture, partnering with solution teams to ensure solutions are auditable, explainable, and production-ready.
  • Technical Due Diligence & Evaluation: Evaluate emerging AI/ML technologies, frameworks, and cloud services for fit within the ADS architecture; lead proof-of-concept efforts and publish technical recommendations to inform platform and tooling decisions.
  • Architecture Review & Governance: Lead architecture review processes for AI initiatives, ensuring design quality, technical debt management, and alignment with enterprise architecture principles before solutions advance to development and production.
  • Stakeholder Communication & Influence: Communicate architectural vision, trade-offs, and technical roadmaps to ADS leadership, business partners, and IT stakeholders; build consensus on technology direction and investment priorities.
Desired Qualifications
  • Advanced degree (Ph.D. or Master’s) in Computer Science, AI/ML, or a related technical discipline
  • Experience in the life and health insurance or reinsurance industry
  • AWS Solutions Architect Professional, Databricks Architect, or equivalent cloud/platform certifications
  • Knowledge of real-world data, medical, underwriting, and other third-party data sources
  • Knowledge of actuarial concepts and the reinsurance or insurance industry
  • Experience with infrastructure-as-code (Terraform, CloudFormation), CI/CD pipelines, and DevOps/MLOps practices
 RGA Reinsurance Company

RGA Reinsurance Company

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