Web Engineering Operations Manager

Renesas Electronics•Austin, TX

15h•Onsite

About The Position

Renesas is seeking a Web Engineering Operations Manager to help lead the operational side of our AI transformation within the Web Engineering organization. This role will focus on turning AI opportunities into structured, prioritized, and scalable engineering work while also strengthening how the team plans, coordinates, and delivers across development, QA, production, and related web workflows. This is a hands-on operations management role for someone who can bring structure to complex technical work, improve engineering operating rhythms, and help move AI from experimentation into practical, scalable delivery. The role will partner closely with the Development Manager, AI Technical Lead, Product AI Lead, QA, Production/DevOps, Product Management, and other cross-functional stakeholders. The ideal candidate combines strong program and operations leadership, excellent communication and reporting skills, and enough understanding of modern web engineering environments to work credibly with technical teams. This person will help define roadmaps, clarify priorities, manage dependencies, improve visibility, create consistent reporting, and ensure follow-through as AI-enabled work becomes an increasingly important part of the team’s core delivery model.

Requirements

5+ years of experience in engineering operations, technical program management, web/software delivery, or a related technical coordination role.
Experience working with web engineering teams, including development, QA, production operations, and product stakeholders.
Strong understanding of modern web development workflows and common delivery practices.
Familiarity with Jira, Confluence, Microsoft 365, and related collaboration or project tracking tools.
Working knowledge of web platforms and technologies such as Next.js, Drupal, CMS workflows, QA processes, release management, and production support.
Demonstrated ability to manage complex cross-functional initiatives with multiple stakeholders and dependencies.
Excellent communication and reporting skills, including the ability to simplify ambiguity, clarify decisions, summarize progress, and create executive-ready updates.
Experience establishing reliable status reporting, meeting cadences, decision logs, and stakeholder communication practices across technical teams.
Ability to partner effectively with technical leads, managers, contractors, product owners, and business stakeholders.
Strong organizational skills with attention to detail, follow-through, and accountability.
Bachelor’s degree or equivalent experience.

Nice To Haves

Experience supporting AI, automation, developer productivity, or AI-enabled workflow initiatives.
Experience helping teams move prototypes or proof-of-concepts into scalable operational processes.
Familiarity with engineering productivity tools, AI-assisted development, workflow automation, or internal tooling.
Experience in B2B, semiconductor, enterprise technology, web platforms, or digital marketing environments.
Experience working with globally distributed teams.
Familiarity with Agile, Scrum, Kanban, or hybrid delivery models.
Experience creating prioritization frameworks, operating models, roadmap processes, or portfolio-level reporting.
Ability to influence without direct authority and build trust across teams with different priorities.

Responsibilities

Turning AI opportunities into structured, prioritized, and scalable engineering work.
Strengthening how the team plans, coordinates, and delivers across development, QA, production, and related web workflows.
Bringing structure to complex technical work.
Improving engineering operating rhythms.
Helping move AI from experimentation into practical, scalable delivery.
Defining roadmaps, clarifying priorities, managing dependencies, improving visibility, creating consistent reporting, and ensuring follow-through as AI-enabled work becomes an increasingly important part of the team’s core delivery model.
Establishing structure, visibility, and execution discipline needed for engineering and AI-enabled work to scale.
Potentially taking on broader operational leadership responsibilities across engineering delivery, planning, and AI-enabled execution over time.