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Senior Software Engineer, AlloyDB Semantic Search

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Summary

Designs and builds semantic search (AI/GenAI) features for AlloyDB, Google's PostgreSQL-based cloud database, working on core engine areas like query processing, indexing, and vector embeddings. Core tech: C/C++/Java, PostgreSQL internals, distributed systems, and RAG/vector search.

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.

As a Software Engineer focusing on semantic search for AlloyDB, you'll have the opportunity to contribute to AI/GenAI features within an innovative, Google open-source PostgreSQL-based database product. You'll play a key role in building new database features that integrate advanced semantic search capabilities.

You'll be instrumental in designing, developing, and implementing semantic search capabilities within AlloyDB, focusing on delivering robust, scalable, and high-performance features.

You'll be involved in bringing novel innovations to the core database engine, including areas like query processing, indexing, and vector embedding. Your work will directly impact our enterprise customers, empowering them to leverage the power of semantic search within their AlloyDB applications.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.
  • Design, develop, and implement semantic search capabilities within AlloyDB, focusing on delivering robust, scalable, and high-performance features.
  • Collaborate with engineers across various teams to understand requirements and build effective semantic search solutions.
  • Take ownership of specific components and contribute to the team's technical discussions, continuously learning and applying best practices.
  • Build new database features that integrate advanced semantic search capabilities.
  • Contribute to key technical projects and work within a fast-moving, innovative environment.

Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 5 years of experience in software development for core system-level software such as databases, operating systems, or kernels.
  • 5 years of programming experience in C, C++ or Java.
  • 3 years of experience building and developing large-scale infrastructure or distributed systems.
  • 3 years of experience with distributed computing.

Preferred qualifications:

  • Master's degree or PhD in Computer Science or related technical fields.
  • 1 year of experience with AI and agentic development.
  • Experience with database internals (e.g., PostgreSQL, GraphQL, OLTP databases), transactional systems, compilers, or data storage.
  • Experience designing enterprise Retrieval-Augmented Generation (RAG) systems, with expertise in vector search, embedding optimization, hybrid search, semantic retrieval, and data grounding strategies.
  • Knowledge of graph algorithms and graph databases.

Skills

See also

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