Like Google's own ambitions, the work of a Software Engineer goes way beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of engineers. You not only optimize your own code but make sure engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way.
With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.
As a part of the Operations Intelligence team, a newly created team at the forefront of transforming how we create, manage, and deliver support content by leveraging data and automation, you will be responsible for building and leading a team of engineers dedicated to designing, developing, and maintaining innovative systems and platforms that automate various aspects of the content life-cycle.
In gTech Users and Products (gUP), our mission is to advocate for Google’s users by creating helpful and trusted experiences across the product ecosystem. We achieve this by meeting partners and consumers where they are with support and help, representing their needs with our product partners and proposing fixes and features that elevate their engagement with Google's diverse product ecosystem. Additionally we provide a range of product services that ensure our products are optimized for every user, no matter where they are in the world (e.g., localization, digitization, partner integration and more). Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $207000 - $301000 (USD) + 20% bonus target + bonus + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Build, mentor, and manage an engineering team focused on content automation, fostering career development, technical excellence, and a collaborative team culture.
- Define and drive the technical strategy, roadmap, and architecture for content automation systems and platforms, evaluating and incorporating innovative technologies to meet business needs.
- Oversee the end-to-end software development life-cycle for the team, ensuring timely and high-quality delivery of scalable, reliable, and maintainable content automation solutions.
- Partner with content strategists, product managers, operations teams, data scientists, and other stakeholders to identify automation opportunities, gather requirements, and ensure solutions deliver maximum impact.
- Advocate engineering best practices, drive high standards for code quality and system design, and encourage innovation in the application of automation technologies (including ML/NLP where appropriate) issues.
Qualifications
Minimum qualifications:
- Bachelor’s degree, or equivalent practical experience.
- 8 years of experience in software development.
- 3 years of experience with full-stack development, across the back-end such as Java, Python, Golang, or C++ codebases, and front-end experience including JavaScript or TypeScript, HTML, CSS or equivalent.
- 3 years of experience in a technical leadership role.
- 2 years of experience in a people management or team leadership role.
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical field.
- 3 years of experience working in a complex, matrixed organization.
- Experience with large-scale data processing and machine learning platforms, including practical application of Generative AI and machine learning optimization techniques.