Senior Manager, AI/ML Engineering & Customer Insights - Frisco

Role Overview: Looking for a role where you can lead, mentor, and still stay hands-on with cutting-edge AI and machine learning technologies? Be ready to build a new AI-powered customer insights capability from the ground up and shape the future of customer experience as we are seeking an innovative and hands-on Senior Manager, AI/ML Engineering & Customer Insights to establish and lead a new strategic function focused on transforming customer experience through data-driven insights and artificial intelligence. This role sits at the intersection of Engineering, Product, Data, and Customer Experience, with responsibility for building capabilities that aggregate and analyze telemetry data, customer feedback, reviews, support signals, and product usage patterns to identify opportunities that improve customer satisfaction, retention, and acquisition. You will define the vision, architecture, processes, and operating model for leveraging AI/ML and Generative AI technologies to uncover actionable insights at scale. You will be both a technical leader and people manager, capable of developing proof-of-concepts, building production-grade solutions, and leading a growing team of engineers and data professionals. The ideal candidate combines deep software engineering expertise with practical AI/ML experience, strong business acumen, and the ability to influence stakeholders across engineering, product, and executive leadership teams. Location Note: This is a Hybrid position located in Frisco, TX. You will be required to be onsite on a regular 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:

• Establish and lead a new AI-driven Customer Insights function within the engineering organization.
• Define the strategy, roadmap, and technical vision for leveraging AI/ML to improve customer experience and business outcomes.
• Partner with Engineering, Product, Customer Experience, and Leadership teams to identify high-impact opportunities and prioritize initiatives.
• Build frameworks, processes, and best practices for insight generation, experimentation, and measurement.

• Design and implement AI/ML solutions that aggregate, analyze, and synthesize data from multiple sources including telemetry, application logs, customer reviews, surveys, support interactions, and product feedback.
• Develop machine learning models, algorithms, and analytical frameworks that identify trends, root causes, customer pain points, and product improvement opportunities.
• Leverage Large Language Models (LLMs) and Generative AI technologies to automate insight generation, sentiment analysis, summarization, classification, and recommendation workflows.
• Build proof-of-concepts and rapidly validate emerging AI technologies before scaling them into production environments.
• Develop approaches to measure the effectiveness and business impact of AI-generated insights.

• Architect and build scalable cloud-native solutions on AWS and/or Azure environments.
• Develop robust data pipelines and processing frameworks capable of handling large-scale structured and unstructured datasets.
• Lead the development of APIs, services, and platforms that support customer insight generation and consumption.
• Ensure engineering excellence through modern software development practices, security, reliability, and operational scalability.
• Drive adoption of MLOps and AI platform best practices for model deployment, monitoring, governance, and continuous improvement.

• Build, mentor, and lead a high-performing team of engineers and data professionals.
• Provide technical guidance, coaching, and career development support.
• Participate in hiring, technical assessments, and team-building activities as the function expands.

• Present findings, recommendations, and business impacts to senior leadership.
• Translate complex technical analyses into actionable insights for non-technical stakeholders.
• Influence product roadmaps and engineering priorities through data-driven recommendations.
• Collaborate closely with global teams and stakeholders to align customer experience initiatives across the organization.

About You:

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Machine Learning, or a related field.
• 10–15 years of software engineering experience with at least 3+ years focused on AI/ML, advanced analytics, or data-driven product development.
• Proven experience leading engineering teams and delivering complex technical initiatives from concept through production.
• Strong hands-on programming experience with Python and modern software engineering practices.
• Demonstrated experience applying AI/ML techniques to solve real-world business problems.
• Experience building scalable cloud-native applications and data platforms in AWS, Azure, or GCP environments.
• Strong understanding of machine learning lifecycle, model deployment, experimentation, and production operations.
• Experience working with large-scale structured and unstructured datasets.
• Strong stakeholder management, communication, and influencing skills.
• Ability to balance strategic leadership with hands-on technical contribution.
• Hands-on experience of Machine Learning, Predictive Analytics, Natural Language Processing (NLP), Large Language Models (LLMs), Prompt Engineering, Retrieval-Augmented Generation (RAG), and AI platforms such as OpenAI, Anthropic, and Hugging Face, with experience developing AI-powered solutions including sentiment analysis, summarization, classification, and recommendation systems.
• Strong software engineering experience with Python and/or Golang, including designing and developing RESTful APIs, microservices, distributed systems, and event-driven architectures.
• Experience building and deploying cloud-native applications using AWS (EKS, Fargate, S3, Lambda), Azure, or Google Cloud Platform (GCP), with expertise in Docker and Kubernetes for containerization and orchestration.
• Strong knowledge of SQL and NoSQL databases, including Microsoft SQL Server, DynamoDB, MongoDB, and Cassandra, along with experience working with big data technologies such as Apache Spark, Hadoop, and Data Lake architectures.
• Experience with messaging and middleware technologies, including Kafka, Redis, and RabbitMQ, to build scalable, high-performance distributed applications.

Success Measures:

Success in this role will be measured by:

• Creation and successful adoption of a customer insights capability.
• Improvements in customer satisfaction and experience metrics.
• Identification and resolution of customer-impacting engineering issues.
• Influence on product decisions through actionable insights.
• Delivery of scalable AI-powered solutions that drive measurable business outcomes.
• Growth, effectiveness, and engagement of the engineering team.

Ideal Candidate Profile

The successful candidate is a builder, innovator, and leader who enjoys creating new capabilities from the ground up. They combine strong engineering fundamentals with modern AI expertise and have the ability to translate large volumes of customer and operational data into meaningful business impact. They are equally comfortable discussing architecture with engineers, product strategy with product leaders, and business outcomes with executive stakeholders.

#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.