Your mission is to build the data and evaluation flywheel for large-scale agentic software engineering: transforming execution trajectories into actionable loss analysis, pioneering automated skill improvement workflows, and hillclimbing agent success rates across complex, multi-repo codebase maintenance tasks (e.g., automated refactoring, proto optimization, dependency pruning, and Mendel flag deprecation).
Your focused areas include but are not limited to the following: AI verifier, quality hillclimbing, agent skill auto-improvement, coding agent evaluation, trajectory analysis, etc. Note this role will not focus on agent infrastructure.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Deliver innovative agentic-first solutions for a self-maintaining codebase, setting the standards for AI-driven productivity at Google.
- Thrive in ambiguity by embracing rapid iterations to validate assumptions and fail fast.
- Collaborate effectively with distributed teams across DE, US, and IND to define technical roadmaps, promote alignments, and oversee project execution.
- Nurture a vibrant team environment anchored in mutual respect and relentless innovation, fostering a psychologically safe space for professional growth.
- Develop a deep understanding of customer needs to balance the requirements of multiple Product Areas (PAs) and bridge the gap with the SMC offering.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience coding with Python.
- 2 years of experience working with Generative AI.
- 2 years of experience working with Large Language Models.
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical fields.
- 2 years of experience with Agentic AI, Evaluation, and quality hill climbing.
- 2 years of experience with prompt engineering; using, interacting, and evaluating AI Agents or LLMs in the coding space.
- Familiarity with code maintenance, migration, and large-scale changes.
- Familiarity with Google latest AI-driven coding tools.