Head of Apps Engineering, Enterprise

This Director of Engineering leads two new teams: AI Developer Experience, which builds tooling and agent workflows to accelerate engineering, and AI Business Enablement, which empowers non-technical staff to create internal apps with AI. The role involves setting strategy, developing managers, and driving adoption of AI-powered development practices across the company. It requires 10+ years of software engineering experience and a strong hands-on background with AI coding agents.

Leads the engineering of enterprise applications, overseeing architecture and development. Manages a team, ensures scalability, and aligns technical work with business needs.

This Staff+ role leads the architecture and development of purchasing and subscription experiences across native mobile (iOS/Android), mobile web, and supporting product APIs. The engineer will drive conversion, performance, and reliability improvements through experimentation and analytics, while building reusable components and setting engineering standards. Requires deep native mobile expertise with demonstrated full-stack contribution.

This role manages a team of Applied AI Engineers supporting enterprise customers. The manager is responsible for team development, technical quality, and operational rigor, coaching engineers on architecture, model selection, and production readiness. They act as a senior escalation point for critical launches and incidents, partnering with Sales, Solutions Engineering, and Product to drive customer success and expansion.

This role owns production ML systems and builds MLOps platform infrastructure for Klover's B2C financial services. The engineer will design and operate pipelines, feature infrastructure, model-serving, CI/CD, and observability to take models from experiment to reliable production. Requires 5+ years of MLOps experience, expertise in GCP/Kubernetes/Terraform, and fluency directing AI coding agents.

This VP-level role owns the scientific methodology behind Attain's measurement products, including causal inference, attribution, and media mix modeling. The leader will set standards for defensibility, represent methodology to clients and partners, and lead a team of data scientists. Requires 10+ years in AdTech/MarTech data science and deep expertise in Bayesian methods and experimental design.

This VP role owns the data product portfolio, including consumer transaction data, marketing science feeds, and extrapolated datasets. The leader will set strategy, manage product managers and execution teams, and ensure scientific defensibility. Requires extensive experience in data products, marketing science, and leading teams, with fluency in causal measurement and AI methods.