Senior AI Engineer, MarTech

McAfee • Frisco, TX

3d • Hybrid

About The Position

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 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 About You: 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 #LI-Hybrid

Requirements

• 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.

Responsibilities

• 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

Benefits

• Bonus Program
• 401k Retirement Plan
• Medical, Dental, Vision, Basic Life, Short Term Disability and Long-Term Disability Coverage
• Paid Parental Leave
• Support for Community Involvement
• 14 Paid Company Holidays
• Unlimited Paid Time Off for Exempt Employees
• 96 Hours of Sick Time and 120 Hours of Vacation for Non-Exempt Employees Accrued Each Year

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 501-1,000 employees