Software Engineer, Acceleration Platform Team
Indexed description
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 1 year of experience with software programming in Python or C++.
- 1 year of experience with data structures and algorithms.
- 1 year of experience implementing core Machine Learning (ML) concepts.
- Experience in AI safety, enterprise security, advanced prompt engineering, and scalable model evaluation methodologies.
- Expertise in distributed systems architecture and core programming, paired with a sophisticated, nuanced understanding of LLM capabilities, limitations, and failure modes.
- A proven track record of designing, deploying, and scaling LLM-backed applications, complex RAG systems, or self-supporting agents in enterprise production environments.
As a key member of a small and versatile team, you design, test, deploy and maintain software solutions.
As a Core Software Engineer in the Acceleration Platform team in Singapore, you will build scalable, AI-native agentic systems that automate complex workflows and eliminate developer toil globally.
In this role, you will manage zero-to-one initiatives, shipping resilient features that solve enterprise-scale engineering problems. You will work alongside executive experts to set new standards in AI engineering, growing skills while ensuring our systems remain secure-by-default and highly performant.
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.
Responsibilities
- Architect agentic ecosystems by leading the design and implementation of highly scalable, fault-tolerant systems where multi-agent networks reason, plan, and execute complex workflows across vast, distributed codebases.
- Pioneer AI-first engineering by defining best practices for the team and broader organization. Blend traditional distributed systems architecture with advanced Large Language Model (LLM) orchestration, complex Retrieval Augmented Generation (RAG) pipelines, and optimization.
- Scale evaluations and guardrails by establishing a comprehensive technical strategy for AI safety, architecting, automated frameworks that measure performance and enforce security to mitigate across large-scale deployments.
- Solve the hardest AI problems through managing the most intricate non-deterministic edge cases. Build advanced telemetry and introspection tooling that allows the entire organization to understand, debug, and optimize self-supporting behavior.
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