Senior AI Engineer, MarTech

Job Title: Senior AI Engineer, MarTech Role Overview: We are looking for a Senior AI Engineer to lead the transformation of our marketing ecosystem. You won’t just be maintaining tools; you will be architecting the intelligence layer that powers hyper-personalization, autonomous campaign optimization, and generative creative pipelines. You will architect and lead buildout of infrastructure systems that do not merely execute pre-defined tasks but perceive context, reason through complex strategic problems, and orchestrate end-to-end workflows with minimal human intervention. We are moving from "campaign management" —a manual, administrative task—to "campaign orchestration" a strategic, supervisory role and invest in effective Human-Agent Teams. This is a position located in the US in either San Jose, CA or Frisco, TX. You will be required to be onsite on an as-needed basis. We are only considering candidates within a commutable distance to one of the two locations and are not offering relocation assistance at this time. About the Role: Architect Agentic Workflows: Design and deploy AI agents to automate complex marketing tasks such as cross-channel campaign orchestration and real-time lead qualification. Generative Asset Pipelines: Build and maintain scalable pipelines for automated ad creative generation (text, image, and video) using LLMs and Multimodal models (Stable Di [... source excerpt omitted ...] nalization: Implement RAG (Retrieval-Augmented Generation) systems to provide context-aware, personalized content across web, email, and SMS. Build Predictive Models: Develop and productionalize ML models for high-impact marketing use cases: LTV (Lifetime Value) prediction, churn propensity, and "Next Best Action" engines. MLOps & Integration: Own the end-to-end lifecycle of models, from feature engineering in SQL/Python to deployment via APIs and monitoring for data drift in production. Privacy & Ethics: Ensure all AI implementations comply with global privacy standards (GDPR, CCPA) and implement "Privacy-First" AI features like differential privacy or synthetic data generation [... source excerpt omitted ...] stem: Hands-on experience integrating AI with CDPs (HighTouch), ESPs (Braze, Iterable), or Ad Platforms (Meta Conversions API, Google Enhanced Conversions), Analytics (Adobe CJA), Customer focused websites (Javascript, Adobe Experience Manager) Data Stack: Mastery of SQL and cloud data warehouses. Experience with Databricks for feature engineering is a huge plus. Generative AI: Proven experience with Claude fine-tuning models (LoRA, QLoRA) and managing vector databases (Pinecone, Milvus, or Weaviate). Deployment: Experience with Docker, Kubernetes, and cloud AI services (AWS SageMaker, Google Vertex AI, or Azure AI Studio). Domain Expertise: Previous experience in a high-grow