AI Engineering Tech Lead

4 weeks ago


Cleveland, Ohio, United States Crowe Full time

About Crowe AI

We're on a mission to make the future of human work more purposeful by leveraging state-of-the-art machine learning, modern architectures, and industry experts to create AI-powered solutions that transform the way we do business.

As a member of our AI Engineering team, you'll be a builder excited to realize an AI idea's impact at scale, distinguishing Crowe in the market and driving the firm's technology and innovation strategy.

About the Team

We foster good science by giving you the time and resources to build your expertise in your project and beyond. You'll guide fellow MLEs and product stakeholders through your work, making good scientists better.

We want to be one of the best options on the job market, which is why we offer regular ethics and book club meetings, monthly lightning talks, support for conferences, and weekly '10P' independent time for ongoing learning.

About the Role

As a Tech Lead in AI Engineering, your responsibilities will vary across the development lifecycle, including providing solutions architecture and vision for existing solutions, supporting new feature development, testing, and preparing for release of high-quality, deployment-ready code.

You'll oversee the implementation of testing protocols, including smoke tests and unit tests, to maintain high-quality outputs, in collaboration with members of the MLOps software engineers.

Prepare and refine Service Level Agreements (SLAs) and release documentation in preparation for production deployment; collaborate with the Enablement team to create user upskilling materials that support effective use and drive adoption of AI solutions and latest features.

Lead ethical reviews and risk/security evaluations to ensure compliance and safeguard our solutions. Engage with business stakeholders to refine project objectives and demonstrate the value and impact of implemented features.

Act as a career coach, fostering the growth and development of team members through knowledge-sharing, constructive code review, and by setting the standard for code quality.



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