The role
From Google's own posting.
In this role as Uber Technical Lead for AI Systems Knowledge and Intelligence Engine (ASKIE), you will define the technical roadmap for improving Agentic AI quality outcomes, driving AI adoption, and guiding key workstreams around building capabilities that address software engineering modernization at Google-scale. You will drive the technical outlook and execution of our ASKIE Strategy, and ensure alignment with broader company goals.
The Core team builds the technical foundation behind Google’s flagship products. We are owners and advocates for the underlying design elements, developer platforms, product components, and infrastructure at Google. These are the essential building blocks for excellent, safe, and coherent experiences for our users and drive the pace of innovation for every developer. We look across Google’s products to build central solutions, break down technical barriers and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $307000 - $427000 (USD) + 30% bonus target + equity + benefits
Learn more about benefits at Google .
Drive the technical outlook of the ASKIE strategy, ensuring alignment with Google-wide goals, and making agentic software development a reality at Google-scale.
Create and evaluate the safety guardrails that enable Google to rapidly adopt GenAI for a broad range of Software Development without the risk of IP exfiltration, system outages, or dilution in code quality.
Set standards for measurement and telemetry of data across various aspects of the SDLC, and influencing Finance and other stakeholders across the company on measuring the efficacy of AI adoption.
Collaborate with senior leaders across Core and Google to discover new opportunities and best practices for applying GenAI technologies.
Represent Google in various academic and industry forums, raising the bar industry-wide for transforming software development through AI.
Minimum qualifications:
Bachelor's degree in Computer Science, Mathematics, or other relevant engineering discipline or equivalent practical experience.
15 years of experience as a software engineer or research scientist.
Experience with large-scale Machine Learning infrastructure, ML or AI for products, or related fields.
Preferred qualifications:
Advanced degree in Engineering, Computer Science, or Mathematics.
Experience in software engineering research, particularly using AI/ML.
Experience delivering complex projects with a bias to action and motivating others at all levels by creating a shared outlook and purpose.
Blend of GenAI at model layer and large-scale software development experience with expertise across Research and Applied ML for code domain.
Understanding of computing, data centers, enterprise software, and hardware infrastructure.
High-degree of cross-organizational collaboration and coordination in a rapidly evolving space like GenAI.
Bachelor's degree in Computer Science, Mathematics, or other relevant engineering discipline or equivalent practical experience.
15 years of experience as a software engineer or research scientist.
Experience with large-scale Machine Learning infrastructure, ML or AI for products, or related fields.