Senior AI Engineer, MarTech

About the role

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. 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.

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.

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.

Qualifications

Previous experience in a high-growth B2C marketing environment.

Strong understanding of Bayesian A/B testing and causal inference to measure the true uplift of AI interventions.

Ability to translate vague marketing goals into specific technical requirements and model objectives.

Experience developing applications or integrations with Windows, MacOS, iOS, Android ecosystems.

Skills

Expert proficiency in Python.

Deep experience with PyTorch or TensorFlow, and LLM orchestration frameworks (LangChain, LlamaIndex).

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).

Mastery of SQL and cloud data warehouses. Experience with Databricks for feature engineering is a huge plus.

Proven experience with Claude fine-tuning models (LoRA, QLoRA) and managing vector databases (Pinecone, Milvus, or Weaviate).

Experience with Docker, Kubernetes, and cloud AI services (AWS SageMaker, Google Vertex AI, or Azure AI Studio).

Benefits

We work hard to embrace diversity and inclusion and encourage everyone at McAfee to bring their authentic selves to work every day. We offer a variety of social programs, flexible work hours and family-friendly benefits to all of our employees.

Bonus Program

401k Retirement

Medical, Dental, Vision, Basic Life, Short Term Disability and Long-Term Disability Coverage

Paid Parental Leave

Support and 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

Pay

The anticipated compensation for this position is USD $135,910.00/Yr. - USD $223,285.00/Yr. depending on experience and qualifications.