Senior Software Engineer - AI Productivity Team

• Lead end-to-end design reviews for high-throughput distributed systems to ensure platform reliability.
• Architect secure, scalable integrations across agent frameworks including Agent Development Kit (ADK), Orcas, and Beyond Agency, and large-scale data engines like F1, GoogleSQL, and BigQuery.
• Define multi-quarter roadmaps for AgentFlux and emerging AI productivity initiatives to align platform capabilities with TFR/PSS strategic priorities.
• Align platform capabilities with Technology Foundations and Research (TFR)/Privacy, Safety, and Security (PSS) strategic priorities and evolving Large Language Model (LLM) infrastructure.
• Establish rigorous service level objectives and automated evaluation baselines using Latinum and Everest to measure platform accuracy, latency, and quota utilization.

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages.
• 3 years of experience building developer tools (e.g., compilers, automated releases, code design and testing, test automation frameworks).
• Experience working with algorithms, data structures, analysis, and software design.
• Experience in a technical leadership role.
• Experience designing system architecture for enterprise computing environments supporting AI/ML workloads.

Preferred qualifications:

• Experience with LLMs, Agentic Architectures, distributed systems, compilers, AST analysis, and database internals.
• Experience designing and maintaining distributed systems, APIs, or developer platforms.
• Experience with LLM evaluation frameworks, benchmarking, prompt engineering pipelines, agent memory management, and tool integration.
• Experience converting developer pain points into scoped architectures, technical milestones, and measurable business impact.
• Experience communicating across distributed, multi-timezone teams and fostering a high-trust engineering culture.
• Experience developing accessible technologies.

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.

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.

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages.
• 3 years of experience building developer tools (e.g., compilers, automated releases, code design and testing, test automation frameworks).
• Experience working with algorithms, data structures, analysis, and software design.
• Experience in a technical leadership role.
• Experience designing system architecture for enterprise computing environments supporting AI/ML workloads.