Senior Software Engineer, AI Platform

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 with end-to-end Machine Learning (e.g., model deployment, model evaluation, optimization, data processing, debugging).
• Experience with AI/ML technologies or infrastructure.
• Experience in building simulation orchestration environments, multi-agent frameworks and tools.
  
• Experience with adopting tracing, logging, and monitoring for agentic workflows.

Preferred qualifications:

• Master's degree or PhD in Computer Science or a related technical field.
• 5 years of experience with data structures and algorithms.
• 1 year of experience in a technical leadership role.
• Experience developing accessible technologies.

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.

In People Operations Engineering (POps Eng), we build the intelligent systems, workflows that power Google’s talent lifecycle and enterprise productivity. Our team bridges research with production-grade software engineering to solve complex organizational problems at Google scale by providing reusable, robust Artificial Intelligence (AI) platform tooling and AI data.

As a Senior Software Engineer on the AI Data and Platform team, you will serve as a key technical contributor designing and deploying reliable Agentic AI systems, Reinforcement Learning workflows, and hallucination-mitigation models. You will play a critical role in developing our enterprise-grade AI platform solutions powering our Agentic solutions. You will directly empower hundreds of internal engineering teams, enabling them to ship high-quality, reliable, and precise AI-motivated capabilities faster.At Corp Eng, we build world-leading business solutions that scale a more helpful Google for everyone. As Google’s IT organization, we provide end-to-end solutions for organizations across Google. We deliver the right tools, platforms, and experiences for all Googlers as they create more helpful products and services for everyone. In the simplest terms, we are Google for Googlers.

Responsibilities:

• Design, write, and deploy production-grade code for multi-agent workflows, tool-use orchestration engines, and dynamic decision-making pipelines.
• Deploy AI frameworks and tools, to enable velocity in product development and scalability of agentic applications that require high-precision and safe execution under complex real-world conditions.
• Build a high-throughput model serving pipelines and real-time execution environments optimized for latency, reliability, and scale. Integrate continuous, data-motivated feedback loops into AI development methodologies. Construct automated testing, evaluation, and observability frameworks to assess agent coverage, monitor regressions, and safeguard product quality across end-to-end workflows.
• Adopt, integrate distributed tracing, data lineage architectures, telemetry into high-volume generative AI data pipelines. Partner with product owners, domain experts to translate challenges into AI solutions.
• Lead feature design reviews, establish coding standards for agentic pipelines. Write maintainable code (e.g., Python, Go etc) to build robust platform abstractions.