Senior AI Engineer, MarTech

McAfee

San Jose, UShybrid$136k-$223k/yrPosted Jun 30, 2026
Posting intelligenceActively listedReposted 18×, possible evergreen/ghost posting

Skills

kubernetesdatabricksjavascripttensorflowlangchainiterablebayesianairflowgrafanapytorchandroiddockergithubpythonopenaiazurebrazeawsllmiosml

About the role

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. Position Details:

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

Pay Range: The anticipated compensation for this position is USD $135,910.00/Yr. - USD $223,285.00/Yr. depending on experience and qualifications. Job Applicant Privacy Notice: Please click here to view and download the Job Applicant Privacy Notice, which applies to all McAfee job applicants who are residents of the state of California.

Compensation

This Machine Learning Engineer role pays $136k-$223k/yr. Within typical range for machine learning engineer roles in United States.

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