Senior Forward Deployed Engineer, Data and AI

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience in a customer-facing technical role (e.g., Forward Deployed Engineer, Solutions Architect, Sales Engineer) leading technical engagements.
• 5 years of experience in software engineering, solution architecture, or technical consulting, including experience writing production level code in one or more programming languages.
• 1 year of experience with Generative AI techniques (e.g., large language models, multi-modal, large vision models) or with Generative AI-related concepts (e.g., language modeling, computer vision).

Preferred qualifications:

• 5 years of experience designing and deploying cloud-native distributed systems, data pipelines, or AI/ML workflows in an enterprise environment.
• 3 years of experience with SQL and modern data warehousing concepts.
• 1 year of experience in prompt development, model evaluation, and the creative application of Artificial Intelligence (AI).

About the job

The Forward Deployed Engineering Team is a specialized product incubation engine dedicated to accelerating product market fit for our unified data cloud and AI capabilities. Tasked with bridging the gap between our powerful platform primitives and the cohesive, high-value solutions enterprises demand, this group operates as a "customer-zero" laboratory.

Composed of expert builders and strategic product leaders, the team operates on a "Co-Invest, Build, Codify" flywheel:

1. Embed deeply with a select group of lighthouse customers.

2. Co-develop breakthrough solutions in real-world environments.

3. Translate these engagements into scalable assets—delivering validated product prototypes to engineering and repeatable go-to-market blueprints to the field.

As a Forward Deployed Engineer (FDE), you contribute to Google's data and generative AI to solve real-world challenges for our most strategic customers. You will act as a partner in tandem with key customers, working directly to build, deploy, and optimize sophisticated Data and AI agents and solutions leveraging Google’s first class technologies. You will bridge the gap between our core product engineering teams and complex customer needs. You will directly accelerate product innovation, customer success, disrupt the traditional SDLC, and shape the future of our Data and AI products.

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.

The US base salary range for this full-time position is $147,000-$216,000 + 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.

Responsibilities

• Contribute to technical architecture for incubation projects. Work to stitch Google’s AI primitives (Vertex AI, BigQuery, Gemini) into high-value solutions like agentic workflows and semantic data layers.
• Support the resolution of ambiguous hurdles that prevent adoption. Debug integration issues, optimize inference latency, and architect security layers to turn "demos" into production-ready assets.
  
• Drive the "codify" phase by transforming bespoke solutions into reusable assets. Author "Golden Path" code repositories and reference architectures to enable the broader ecosystem to scale your work.
  
• Serve as the technical source of truth for core engineering. Document API friction and feature gaps to directly influence the roadmaps of BigQuery, Vertex, and Looker.
• Partner with customer Chief Technology Officers and Chief Data Officers to validate technical feasibility and align our proposed architectures with their existing enterprise stacks.