Senior AI Engineer, MarTech

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 Company Overview McAfee is a leader in personal security for consumers. Focused on protecting people, not just devices, McAfee consumer solutions adapt to users' needs in an always online world, empowering them to live securely through integrated, intuitive solutions that protects their families and communities with the right security at the right moment. Company Benefits and Perks: 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 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 We're serious about our commitment to diversity which is why McAfee prohibits discrimination based on race, color,