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McAfee

Antivirus and cybersecurity software provider

Lead AI Engineer - Ecommerce Engineering

AI Application Engineering +1Updated on Nov 10
Full-timeFrisco, TX, USA

About the Job

Requirements

  • At least 8 years of application development experience.
  • Experience designing, developing, and architecting large-scale production applications and distributed systems.
  • Hands-on experience shipping applications powered by large language models.
  • Experience with production retrieval-augmented generation systems, artificial intelligence agents, or large-language-model-integrated internal tools, including prompt design, retrieval and grounding, evaluations, and operational reliability.
  • At least 3 years of data engineering and analysis experience.
  • Experience building production data pipelines, ETL/ELT workflows, and analytics platforms that turn raw operational and business data into actionable insights.
  • Experience shipping production agents, retrieval-augmented generation systems, and large-language-model-integrated tools with sound judgment on tool use, guardrails, evaluations, and reliability.
  • A track record of using artificial intelligence to measurably reduce toil and accelerate incident response, translating operational needs into solutions teams adopt.
  • Experience with SQL and Spark or PySpark for production pipelines across large-scale datasets.
  • Experience with Python, ETL/ELT orchestration, and data modeling for analytics and operational telemetry.
  • Experience with modern data lakehouse platforms such as Databricks or Snowflake, or similar, and real-time and event-driven processing.

Responsibilities

  • Design a unified operational intelligence platform that combines system signals, including latency, errors, integration and data-flow health, with commercial performance, including conversion, checkout, auto-renewal, and feature adoption, in one trusted source of truth.
  • Bring data from eCommerce, marketing technology, observability, and operational data stores into an analytics-ready and AI-ready state through ETL/ELT pipelines, SQL, and data models, with automated quality validation to power operational intelligence, key performance indicators, and cross-team reporting.
  • Surface standardized engineering metrics across teams, including delivery velocity, quality, security posture, incident trends, and service ownership.
  • Ship AI agents that detect anomalies, surface critical issues with actionable context, and drive intelligent triage that accelerates root-cause analysis.
  • Build AI productivity tools that help teams ship faster and operate more reliably, including root-cause-analysis assistance, intelligent search across telemetry, and code and runbook copilots.

Desired Qualifications

  • A track record of identifying and spreading AI use cases across engineering teams.
  • Strong cross-functional partnership across Product, Site Reliability Engineering, Security, and Architecture.

About the Company

McAfee

Antivirus and cybersecurity software provider

McAfee creates cybersecurity software to protect computers and other devices from malware and online threats. Its products scan for viruses and malware, monitor systems in real time, and use up-to-date threat intelligence to block risky activity. Many offerings are managed through cloud-based services that let people and organizations deploy protection across multiple devices and users. McAfee distinguishes itself through its long history in antivirus, broad consumer and business product lines, and its move from a standalone company to an Intel-backed security division and back to an independent public company, giving it experience across both home and enterprise markets. The company’s goal is to help people and organizations stay safe online by defending devices, data, and identities from cyber threats.

Company size
5,001-10,000
Company stage
IPO
Headquarters
San Jose, CA
Founded
1987

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