Forward Deployed Engineer, Cloud Applied AI
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Minimum qualifications:
- Bachelor’s degree or equivalent practical experience
- 2 years of experience in software development.
- 2 years of experience in testing/launching software products and in software design/architecture.
- 2 years of experience with speech/audio, reinforcement learning, or ML infrastructure.
- Experience with core GenAI concepts (LLM, Multi-Modal, Large Vision Models).
Preferred qualifications:
- Master’s degree or PhD in Engineering or Computer Science.
- Experience in Vertex AI, BigQuery, Cloud Storage, and Dialogflow.
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.
The Applied Artificial Intelligence (AAI) organization is Google Cloud's engine for transforming business with groundbreaking packaged generative AI solutions.
Responsibilities
- Partner directly with strategic customers to design, co-develop, debug, and deploy AI agents and solutions.
- Act as a high-level problem solver, empowered to write bespoke code, develop custom tooling, and contribute directly to the core product codebase.
- Systematize learnings from customer engagements working with AAI team members to create reusable tools, robust documentation, and accelerators.
- Serve as a critical feedback loop to core Product and Engineering teams, and synthesize field insights to influence strategy
- Provide technical guidance on agent improvement, performance tuning, CI/CD pipelines, and production readiness.
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