Director of Engineering for CodeAI
Google· enterprise· Internet & Cloud Services· Sep 3, 2026 · 2mo ago
San Jose, CA, USA
In office
Full-time
Director
$210K–$270K est.
15+ years exp
Job description
As the Director of Engineering for CodeAI, you will partner deeply with DeepMind (GDM) to lead the technical strategy for bringing frontier AI capabilities to enterprise scale product development workflows.
Your mission is to frame and lead research and Applied AI efforts to make Gemini better for Google scale product development workflows, and to bridge the gap between model breakthroughs and production-grade development agents and solutions that drive user delight and accelerate innovation velocity for Google product areas.
You will lead a high-velocity organization responsible for cutting-edge coding agent research and technologies (with active partnerships with GDM) and evaluation, validation systems to ensure recursive self improvement is landed for model and product building at Google.
The successful candidate will develop and execute on the strategic vision for landing recursive self-improvement at Google scale.
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 .
• Serve as a high-bandwidth partner for research teams in DeepMind in identifying critical gaps in core intelligence pieces - LLM, harness and adjacent capabilities (memory, context engineering, recursive self-improvement loops), activating and successfully executing on research and development work to improve LLMs+ adjacent pieces for Google scale critical user journeys.
• Translate frontier capabilities into high-value product capabilities that professionals love and set up feedback flywheel to extract and upstream rich expert signal to GDM (e.g., high-quality, high-complexity datasets that can unlock model hill-climbing for higher level of autonomy for complex tasks).
• Build, scale, and inspire an organization of frontier AI-native engineering by maintaining focus on fast pace of experimentation/iteration and identifying the biggest blockers to getting to AGI, partnering with GDM to land research and value breakthroughs at Google scale, through first-principles thinking.
• Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience
• 15 years of professional experience in software engineering
• 10 years of experience in senior leadership roles leading frontier research or applied AI engineering teams
• 3 years of experience experimenting and landing GenAI products
• Experience with concepts such as hill-climbing for quality, fine-tuning/SFT, and agentic systems
• Experience leading and translating frontier AI research into production-grade enterprise GenAI products/agents
Minimum qualifications:
• Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience
• 15 years of professional experience in software engineering
• 10 years of experience in senior leadership roles leading frontier research or applied AI engineering teams
• 3 years of experience experimenting and landing GenAI products
• Experience with concepts such as hill-climbing for quality, fine-tuning/SFT, and agentic systems
• Experience leading and translating frontier AI research into production-grade enterprise GenAI products/agents
Preferred qualifications:
• Master's degree of PhD in Machine Learning, Computer Science, or a related discipline
• Demonstrated impact through leading high-velocity, high-calibre, mission-driven teams, especially those that interface with a frontier research organization
• Established presence and thought-leadership in the AI/ML community, demonstrated through landed value by high-impact research or high-value Applied AI products/agents
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