Lead AI Engineer – eCommerce Engineering

Role Summary

Join our eCommerce Engineering Intelligence team as a Lead AI & Data Engineer. You’ll be the hands‑on technical builder behind two strategic initiatives: a unified data platform that shows how eCommerce is performing —technically and commercially — and our AI enablement strategy across engineering, shipping agents and productivity tools that teams rely on every day.

This is a Hybrid position located in Frisco, TX. You will be required to be on‑site on an as‑needed basis; when you are not working on‑site, you will work from your home office. You must be within commutable distance of Frisco, TX. We are not offering relocation assistance at this time.

• Design a unified operational intelligence platform — an eCommerce Health view that combines system signals (latency, errors, integration and data‑flow health) with commercial performance (conversion, checkout, auto renewal, feature adoption) in one trusted source of truth.
• Bring data from eCommerce, Mar Tech, 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 — powering operational intelligence, KPIs, and cross‑team reporting.
• Surface standardized engineering metrics across teams — delivery velocity (DORA‑style), 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 — RCA assistance, intelligent search across telemetry, code and run‑book copilots.

• 8+ years in application development.
• Designing, developing, and architecting large‑scale production applications and distributed systems.
• Hands‑on experience shipping LLM‑powered applications.
• Production RAG systems, AI agents, or LLM‑integrated internal tools – including responsibility for prompt design, retrieval/grounding, evals, and operational reliability. Track record of identifying and spreading AI use cases across engineering teams is a strong plus.
• 3+ years in data engineering and analysis.
• Building production data pipelines, ETL/ELT workflows, and analytics platforms that turn raw operational and business data into actionable insights.

• Agentic AI and LLM application engineering – shipping production agents, RAG systems, and LLM‑integrated tools with sound judgment on tool‑use, guardrails, evals, and reliability.
• Efficiency‑driven impact – track record of using AI to measurably reduce toil and accelerate incident response, translating operational needs into solutions teams adopt.
• Strong cross‑functional partnership across Product, SRE, Security, and Architecture.

• Expert SQL and Spark/PySpark for production pipelines across large‑scale data sets (billions of rows).
• Strong Python, ETL/ELT orchestration, and data modeling for analytics and operational telemetry.
• Modern data lake house platforms (Databricks, Snowflake, or similar), real‑time and event‑driven processing.

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 protect their families and communities with the right security at the right moment.

• Bonus Program
• 401(k) 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 accrued each year.

The anticipated compensation for this position is USD $/Yr. – USD $/Yr. depending on experience and qualifications.

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