Software Engineer III, GenAI, Vertex RAG Engine

Google • Sunnyvale, CA

3h • $141,000 - $202,000

About The Position

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.

Retrieval Augmented Generation is a technique that enhances large language model
(LLM) outputs by referencing authoritative, external knowledge bases before
generating responses.

Today, Vertex AI Retrieval-augmented generation (RAG) Engine is a fully managed
orchestration platform for building RAG solutions, allowing users to choose the
RAG building components based on their business need and power RAG use cases in
LLM and Agents. It aims to become an easy-to-use, enterprise-ready,
fully-customizable, OSS-compatible, high-performance and scalable RAG service.

We had a growth in product adoption and usage, with more advanced requirements
and challenges. We are building Agentic RAG, Multimodal RAG, and Graph RAG
offerings, and also evolving RAG Engine to become a more comprehensive search
platform to bring developers with a unified experience in building RAG, search,
and Agents.

The US base salary range for this full-time position is $141,000-$202,000 +
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 [https://careers.google.com/benefits/].

Requirements

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
• 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
• Experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
• Experience designing and implementing scalable data pipelines for high-volume data processing.
• Experience building and deploying information retrieval systems in production.

Nice To Haves

• Master's degree or PhD in Computer Science or related technical fields.
• 2 years of experience with data structures or algorithms.
• Experience developing accessible technologies.

Responsibilities

• Write product or system development code.
• Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
• Implement GenAI solutions, utilize ML infrastructure, and contribute to data preparation, optimization, and performance enhancements.
• Evaluate and ensure end-to-end retrieval and generation quality. Improve indexing and retrieval performance.
• Build AI applications/agents for both proof-of-concept and solving real business need.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level