Senior Manager, Computer Vision

Rockwell Automation•Mayfield Heights, OH

1d•$153,280 - $229,920•Remote

About The Position

Rockwell Automation is building machine vision and visual inspection into the Automation Control Software portfolio, alongside Studio 5000 Logix Designer, FactoryTalk Optix, and Data Mosaix. You will lead the engineering organization that builds it - cloud services, edge runtime, front end, and the machine learning that sits underneath - and you will own the roadmap commitments that come out of it. This is a leadership role for someone who still reads the code. You will be the technical center of gravity across subsystems, run the escalation path for hard customer issues, and make the calls on architecture, sequencing, and what does not get built. You will run a team whose economics are changing as agents take on more of the implementation, and you will own the call on where human review gates belong - the agent harness, the eval suites, and what 'done' means for AI-generated change on a product customers run in production. GitHub Copilot Enterprise, Claude, and MCP-based tooling are in daily use across the organization. This role will have a remote schedule and will report to the Vice President, Software Engineering.

Requirements

Bachelor's Degree or equivalent years of relevant work experience.
Legal authorization to work in the US is required. We will not sponsor individuals for employment visas, now or in the future, for this job opening.

Nice To Haves

Typically requires 5+ years of related experience in a software product development environment, including leading engineers.
Bachelor's or advanced degree in Computer Science, Engineering, or a related technical discipline.
Experience leading software engineering teams that ship and support a commercial product
Experience owning technical architecture decisions across more than one subsystem
Background as a hands-on engineer before moving into leadership, with retained technical depth.
Experience across both cloud services and edge or embedded software in the same product.
Experience running a customer escalation path and turning field issues into engineering priorities.
Track record building engineering practices - review standards, release quality gates, developer tooling.
Exposure to industrial automation, machine vision, or another domain with physical-world consequences for defects.

Responsibilities

Lead and grow a multi-disciplinary software engineering team spanning cloud, edge, front end, and machine learning.
Own delivery commitments - scope, sequence, and predictability - and communicate risk and tradeoffs to product and executive stakeholders.
Drive architectural direction across subsystems and arbitrate the decisions that cross team boundaries.
Own the second-level technical escalation path for customer-impacting issues and close the loop back into the product.
Partner with product management on roadmap definition, feature detail, and release content.
Set the engineering practices standard: review gates, quality bar, eval coverage for AI-assisted change, and how the team measures its own throughput.
Hire, develop, and retain engineering talent, and build the technical leadership bench underneath you.