Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 7 years of experience leading technical project strategy, ML design, and working with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- Experience with large language models (LLMs), including prompt engineering, agent development, evaluation frameworks, and deployment.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- Experience driving organization-wide initiatives (e.g., migration to new stacks, infra-wide efficiency drives) that deliver measurable improvements to engineering velocity and business outcomes.
- Experience with cross-organizational collaboration and balancing engaging priorities, with a passion for advancing safe, beneficial AI systems through creative technical applications.
- Proficiency in C++, Java, or Python, with a track record of shipping production-grade code to users.
- Ability to partner with product area leadership (Directors/Principal Engineers) to translate ambiguous business ambitions into standardized technical roadmaps.
About the job
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
We are a part of the DevAI team and our mission is to accelerate Google’s transformation into an AI-native company. We partner directly with Google Product Areas to identify, build, and elevate AI capabilities as the foundation to achieve strategic goals. By working at the intersection of product needs and executive strategy, we accelerate time-to-value and eliminate fragmented, one-off solutions.
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.
The US base salary range for this full-time position is $207,000-$300,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
- Partner with leadership to decompose high-level business ambitions into scalable technical blueprints.
- Lead the design and implementation of autonomous, agentic workflows to solve the most complex non-linear challenges.
- Be responsible for delivering model context protocol servers, sub-agents, skills, connectors, agentic wrappers, and safety guardrails required to move agents from experimental pilots to production-grade reliability.
- Codify repeatable deployment patterns and drive insights to Product and Engineering.
- Identify high-value agents, skills, or connectors built in isolation and re-engineer them as scalable capabilities. Turn one-off wins into universal standards that harden and expand Google’s engineering ecosystem.