Senior Manager, Quality Engineering (Intelligent Automation)

Chipotle•Columbus, OH

2d•$130,000 - $193,000•Hybrid

About The Position

The Senior Manager, Quality Engineering (Intelligent Automation) will lead the strategy, development, and evolution of AI-enabled quality engineering practices across Chipotle IT. This role will drive intelligent automation and agentic solutions into the software development lifecycle, partnering across teams to improve product quality, engineering velocity, release confidence, and operational resilience across customer-facing and enterprise platforms.

Requirements

8+ years of working experience in a senior SDET, software development, or similar role.
3-5 years of relevant management experience.
Experience developing and scaling AI-forward engineering strategies within quality engineering, software engineering, or platform engineering organizations.
Experience evaluating, implementing, or scaling fully agentic or semi-agentic solutions, including autonomous workflows, orchestration patterns, intelligent copilots, or AI-based decision support in engineering processes.
Familiarity with LLM-powered development and testing use cases, and experience evaluating AI/ML-enabled tools and platforms that improve engineering productivity, product quality, and operational resilience.
Strong understanding of governance, risk, and controls for enterprise AI adoption, especially regarding security, privacy, compliance, and reliability.
Experience using production telemetry, observability, and quality signals to enable predictive or adaptive quality engineering.
Proven track record of implementing intelligent quality engineering and automation strategies for highly complex, distributed systems.
Strong desire to build and lead teams while creating a culture of problem-solving, ownership, and collaboration across large-scale engineering environments.
Strong working knowledge of object-oriented analysis and design, SOLID principles, and modern software architecture patterns.
Proficiency with cloud technologies (either AWS or Azure).
Experience with observability solutions and platforms including, but not limited to, Splunk, DataDog, Prometheus, Grafana.
Experience with languages such as JavaScript and/or TypeScript, C#, SQL, Powershell.
Experience with modern test automation solutions including, but not limited to, Playwright, Cypress, wdio, Postman.
Experience with test automation SaaS providers including, but not limited to, Saucelabs, Browserstack.
Experience with Azure or AWS DevOps, Agile process improvement, CI/CD pipeline management and automation, NPM, or other package managers.
Have excellent communication and interpersonal skills to collaborate effectively with all business units.

Responsibilities

Drive an AI-forward quality engineering strategy, incorporating generative AI, intelligent automation, and agentic solutions to improve test design, coverage, defect detection, triage, and release confidence.
Evaluate, pilot, and scale AI-enabled and agentic QE solutions, including autonomous or semi-autonomous workflows for test creation, maintenance, execution, monitoring, and analysis.
Establish governance and guardrails for the responsible use of AI in quality engineering, including reliability, security, privacy, explainability, and human oversight.
Partner with engineering, product, data, and platform teams to embed AI-forward quality practices into SDLC, CI/CD, observability, and production validation.
Lead the evolution from script-based automation to intelligent quality systems that use data, telemetry, and predictive insights to proactively identify and mitigate quality risks.
Directly contribute to Chipotle’s success across our most visible customer-facing solutions both online and in-restaurant.
Drive scalable design patterns and implementations that can be re-used throughout the organization.
Create and enhance quality insights, reporting, and dashboards that provide visibility into engineering performance, product quality, and delivery risk.
Use systems thinking and data-driven analysis to understand the scenarios, configurations, and customer journeys that impact product quality.
Develop future leaders on the Quality Engineering team, expand their skills, and embrace servant leadership by removing roadblocks, giving team members autonomy and ownership.
Work with other leaders in software development, product management, cloud/infrastructure, application support, and data, insights, & analytics teams to help define solution and application performance requirements.