About the Role:
Design a unified operational intelligence platform — an eCommerce Health view that combines system signals (latency, errors, integration and data-fl ow health) with commercial performance (conversion, checkout, auto renewal, feature adoption) in one trusted source of truth
Bring data from eCommerce, MarTech, observability, and operational datastores 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
About You :
Experience:
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
AI & Engineering Operational Excellence (Must-Have):
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
Core Data Engineering Skills (Must-Have):
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
#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.:
We're serious about our commitment to diversity which is why McAfee prohibits discrimination based on race, color, religion, gender, national origin, age, disability, veteran status, marital status, pregnancy, gender expression or identity, sexual orientation or any other legally protected status. 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.