Senior AI Engineer, MarTech

• 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 Diffusion, GPT-4o, Sora) while ensuring brand-safe guardrails.
• Real-time Personalization: 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.
• Governance: Implement robust Responsible AI frameworks to ensure that the speed of automation does not compromise the trust of the customer

• Languages & Frameworks: Expert proficiency in Python. Deep experience with PyTorch or TensorFlow, and LLM orchestration frameworks (LangChain, LlamaIndex).
• MarTech Ecosystem: 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-growth B2C marketing environment.
• Experimentation Mindset: Strong understanding of Bayesian A/B testing and causal inference to measure the true uplift of AI interventions.
• Strategic Thinking: Ability to translate vague marketing goals ("we want to increase engagement") into specific technical requirements and model objectives.
• Customer TouchPoints: Experience developing applications or integrations with Windows, MacOS, iOS, Android ecosystems.

The Stack You'll Work With

• Data Foundation: Databricks, HighTouch
• AI/ML Engine: Claude, PyTorch, Hugging Face, OpenAI API, LangGraph
• Orchestration: Airflow, Prefect, or GitHub Actions
• Marketing Execution: Braze
• Monitoring: Weights & Biases, Arize, or Grafana
• Analytics: Adobe CJA

3.73.7 out of 5 stars San Jose, CA 95002 Hybrid work $135,910 - $223,285 a year - Full-time