Team Lead, Software Engineering

Rockwell Automation•Mayfield Heights, OH

19h•Hybrid

About The Position

Rockwell Automation is looking for a Team Lead, Software Engineering, reporting to Sr Manager, Software Engineering. You will develop industry-leading agentic and AI-first capabilities within FactoryTalk Design Studio. These capabilities will allow customers to dramatically improve engineering productivity, quality, and speed. You will lead a team of engineers building agentic, AI-first features that transform how industrial engineers design their workflows throughout their development cycle. You will combine deep hands-on technical leadership with people leadership – driving technical direction, working with lead principal architects, and delivering outcomes with high velocity and quality. You will foster an inclusive, high-performing team culture that keeps pace with the evolving AI landscape. This is a hands-on technical leadership role. Expect to stay close to the code by designing, building, and troubleshooting production AI-enabled software alongside the team (not just guiding from a distance). You will ramp up quickly in new domains and form opinions from evidence. You will guide the team forward, especially in the agentic AI space. You will work with Product Management, UX, and Architecture to bring AI-enabled experiences from concept through production, aligned with Rockwell Automation's strategy for digital transformation and industrial autonomy. As generative AI reshapes how engineers work, this role is critical to ensuring Rockwell Automation leads in delivering AI capabilities that enhance human expertise, accelerate engineering workflows, and improve quality and consistency at scale.

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 2+ years of relevant experience in software leadership functions, including experience developing software engineers in a product development environment
Knowledge of AI trends and capabilities is necessary. This includes hands-on familiarity with modern foundation models/LLMs, embeddings, and common patterns, such as RAG, tool/function calling, and prompt engineering. Additionally, it involves understanding their practical tradeoffs in production software.
Background in software engineering, including modern object-oriented, cloud-native architectures, and technology like Python and TypeScript
Experience learning quickly in new technical domains and leading decisions with confidence
Experience building or integrating agentic AI systems, multi-agent orchestration or generative AI features into production software
Experience with cloud platforms (e.g., Azure), APIs, and distributed systems
Knowledge of human-centered design principles and AI-assisted user experiences
Prior experience with automation software or industrial automation workflows

Responsibilities

Lead a team of software engineers, providing clear technical direction, decision-making and meaningful coaching, and career development
Deliver agentic AI and generative AI features integrated into FactoryTalk Design Studio, from requirements through release.
Guide architectural decisions for AI-enabled systems, balancing scalability, security, performance, and usability
Contribute hands-on through design reviews and code reviews, code implementation, and technical innovation
Collaborate with Product Management and UX to translate customer problems into high-value AI-assisted workflows
Keep pace with this evolving field and quickly apply new developments to production systems.
Increase adoption of modern engineering practices, including CI/CD, automated testing, and DevSecOps and evolve our practices to support generative AI development
Translate complex technical concepts into clear guidance for teams and partners
Ensure solutions meet Rockwell Automation standards for quality, security, and compliance
Partner with platform, cloud, and data teams to integrate AI services, models, and pipelines into production software
Promote a culture of continuous improvement, experimentation, and learning
Communicate with partners, providing transparency on progress, risks, and outcomes