Engineering Manager, Agent Discovery & Commerce Engineering

Ulta Beauty, Inc.•Bolingbrook, IL

11d

About The Position

The Engineering Manager, Agent Discovery & Commerce Engineering leads the engineering team responsible for AI-powered discovery and agentic commerce capabilities across external AI channels, partner ecosystems, and core commerce platforms. Product owns the guest problem, priorities, and business outcomes; this role owns people leadership, the technical roadmap, delivery execution, quality, and production operability, while partnering with Enterprise Architecture on enterprise patterns. This role builds reusable agentic platform capabilities, common APIs, and integration patterns; takes capabilities from pilot to scalable production; and ensures security, observability, service-level objectives (SLOs), resilience, incident management, cost efficiency, and peak readiness. The manager is accountable for hiring, coaching, performance management, succession planning, team capacity, and developing engineers and technical leads.

Requirements

Bachelor’s degree in Computer Science, CIS, Engineering, or equivalent professional experience.
8+ years of experience in product development, software engineering, digital technology, or a related technical field.
5+ years of experience managing technology teams in a complex environment.
Experience leading technical, engineering, and analytical teams, including coaching, performance management, capacity planning, and team development.
Proven experience with agile, continuous delivery, iterative methodologies, sprint planning, backlog management, release planning, and delivery execution.
Solid experience with hybrid and cloud environments, including cloud-native applications, APIs, microservices, SaaS platforms, and enterprise integrations.
Experience leading engineering delivery for AI-enabled, agentic, digital commerce, or other emerging technology capabilities.
Working knowledge of agentic engineering concepts, including agent orchestration, tool and API integration, search and retrieval, evaluations and guardrails, and external AI platform integrations.
Proven experience eliciting requirements and translating product priorities into technical plans, system requirements, and delivery commitments.
Solid experience preparing technical documentation, architecture summaries, solution designs, system specifications, and operational-readiness materials.
Demonstrated experience using approved AI tools to improve engineering productivity, technical execution, delivery planning, documentation, testing, and release readiness.
Strong judgment in applying AI-assisted outputs responsibly, including reviewing for accuracy, protecting sensitive information, following company security standards, and maintaining accountability for final decisions.
Demonstrated experience in process modeling, workflow improvement, delivery optimization, and continuous improvement practices.
Understanding of lifecycles across digital products, pilots, AI-enabled capabilities, platform services, and production systems.
Experience supporting capabilities from pilot through production, including testing, security, observability, reliability, release readiness, incident response, and operational support.
Demonstrated ability to think strategically about business, product, guest experience, AI, commerce, and technical challenges.
Excellent analytical and troubleshooting skills, with the ability to solve complex problems efficiently and guide teams through technical ambiguity.
Excellent communication skills, with the ability to work effectively with non-technical business partners, Product, Architecture, Operations, senior leaders, and cross-functional stakeholders.
Ability to motivate teams, establish accountability, and drive desired results.
Strong experience establishing engineering practices, delivery routines, quality standards, and operational-readiness processes.
Demonstrated ability to present recommendations, risks, tradeoffs, investment needs, and delivery updates to senior leaders to support effective decision-making.
Experience working with consultants, vendors, and teams in an onshore/offshore delivery model.
Proven track record of delivering reliable, high-quality solutions against committed timelines.
Flexibility to provide support during off-hours, weekends, and peak seasons as needed.

Responsibilities

Manage the engineering delivery cadence, including technical backlog readiness, sprint planning, release coordination, technical checkpoints, demonstrations, and status reporting.
Ensure required engineering artifacts and governance evidence are complete and current, including solution designs, architecture decision records, interface contracts, test plans, release checklists, and operational runbooks.
Establish and report engineering measures for delivery predictability, defect trends, platform reuse, partner onboarding time, availability, latency, quality, incident trends, and cost efficiency.
Manage consultants, vendors, and onshore/offshore partners against clear deliverables, quality standards, productivity expectations, budgets, and contractual commitments.
Evaluate emerging technologies, platforms, and partner solutions; recommend adoption based on guest and business value, technical fit, scalability, risk, and total cost of ownership.
Maintain visibility into technical debt, platform lifecycle, and deprecation plans, with clear priorities and remediation paths.
Apply approved AI tools responsibly to improve engineering productivity, quality, and delivery effectiveness across planning, documentation, development, testing, and incident analysis.
Prepare and present engineering recommendations, delivery updates, investment needs, and key risks to senior leaders and governance forums.