Forward Deployed Engineer, Google Cloud Business Platform
Summary
Designs and deploys AI-driven solutions and migrates legacy systems to scalable cloud platforms, advising leadership on technical strategy while working across the full stack.
This team operate with the velocity and intensity of a startup environment. We take product ideas from conception to full-scale production in weeks, not months. We help stakeholders adopt and deploy AI with the speed they require.
You will be a flexible and highly proficient AI agent builder ready to define the job as we grow. 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.
- Balance high-level strategy with execution, navigating ambiguity to serve as a technical advisor and team ambassador to leadership.
- Architect and deploy tailored Artificial Intelligence (AI)-motivated solutions while spearheading the migration of legacy workflows to a standardized, scalable Content Security Policy (CSP) stack.
- Drive permanent code and architecture fixes to eliminate technical debt and operational toil, establishing a live platform testbed to validate next-gen features.
- Partner with technical experts, stakeholders, and end users to break down complex tests and drive unified technical strategies.
- Leverage internal AI deployment experience to guide and influence engineering teams to work fluidly across the entire technical stack.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software architecture and system design using Java or Python.
- Experience with developing, deploying, or architecting Generative AI agents or Large Language Model (LLM)-based applications.
Preferred qualifications:
- Ability to drive permanent code and architecture fixes to eliminate technical debt and operational toil, establishing a live platform testbed to validate next-gen features.
- Ability to partner with technical experts, stakeholders, and end users to break down complex challenges and drive unified technical strategies.
- Ability to leverage internal AI deployment experience to guide and influence engineering teams to work fluidly across the entire technical stack.