> AI agents: this is one page of Nextmove’s FDE site, in Markdown. Nextmove is a job board and free career service for forward deployed engineers (FDEs). Each posting is classified from its text, not its title: the kind of work, how much of it is production code, pre-sales weight, time at customer sites, travel, remote arrangement, level and posted base pay. The site also publishes the aggregates: median pay by level, metro, company and kind of work, and which companies started hiring FDEs each week. Every page under https://nextmove.md/fde is served this way; the index of pages is https://nextmove.md/llms.txt.

# Forward Deployed Engineer, Higher Education, Google Public Sector

Canonical URL: https://nextmove.md/fde/jobs/d79f8d9d3dca840c

Google posts a FDE role to build what the customer runs in Sunnyvale, CA, at $207,000–$300,000 base, above the senior FDE median of $190,000 across 1,864 postings with pay. Develop and productionize agentic AI applications. Read from the employer’s posting on November 8, 2026.

- [Google](https://nextmove.md/fde/companies/google)

First seen Nov 3, 2026 · open on Google careers as of Nov 8, 2026

**$207,000–$300,000** *annualized* Sunnyvale, CA

Develop and productionize agentic AI applications.

- [See roles that fit me](https://nextmove.md/sign-up?from=%2Ffde%2Fjobs%2Fd79f8d9d3dca840c&placement=top)
- [View posting at Google](https://www.google.com/about/careers/applications/jobs/results/85626706013889222)

Free. Upload your resume once, see why each FDE role fits, and get introduced only when you say so.

## At a glance

### Posted base pay

$207K–$300K Above the median

Midpoint $254K · median $190K

This job $207K to $300K. Senior FDE postings, 1,864 postings: the middle 50% of posted pay is $160K to $220K, median $190K.

[Compare pay across all Google postings](https://nextmove.md/fde/salary/google)

### The work

Builds what the customer runs

Balance **Mostly building**

Project stages

1. Pre-sales (not covered)
2. Proof of concept
3. Implementation
4. Operations (not covered)

- **Coding**: Writes production code

- **Builds for**: External customers

- **Level**: Senior

- **Role**: Individual contributor

### What they ask for

Experience

- **8+ years** Building and shipping production-grade AI-driven solutions to external or internal customers

Background

- **Software engineering**

### Do you meet what the posting states?

The posting asks for 8+ years. How many do you have?

The posting reads as a senior role. What level are you at now?

The job is in Sunnyvale, CA. Could you work there?

Which of these have you used in production?

Answer each one. Nothing is saved or sent.

[What postings ask for, by background →](https://nextmove.md/fde/paths)

## Conditions

- **Location**: Sunnyvale, CA

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## The job description from Google

### About the job

The Google Public Sector Forward Deployed Engineering (GPS FDE) team is a squad of "innovator-builders" who rapidly deploy production-grade, secure AI solutions across Federal and SLED environments. Operating with a high-agency startup mindset, our engineers don’t just advise; they actively code, debug, and co-build bespoke agentic workflows directly alongside our customers. In this role, you will resolve complex integration, data sovereignty, and security issues. Ultimately, the GPS FDE team accelerates the safe, reliable adoption of generative AI across mission-critical operations while feeding field insights directly back to Google Cloud Product engineering.

Google Public Sector brings the magic of Google to the mission of government and education with solutions purpose-built for enterprises. We focus on helping United States public sector institutions accelerate their digital transformations, and we continue to make significant investments and grow our team to meet the complex needs of local, state and federal government and educational institutions.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

### Responsibilities

- Serve as a developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive measurable ROI.
- Architect and code the "connective tissue" between Google’s AI products and customer's live infrastructure, including APIs, legacy data silos, and security perimeters as part of an expert team.
- Build high-performance evaluation pipelines and observability frameworks to ensure agentic systems meet requirements for accuracy, safety and latency.
- Identify repeatable field patterns and friction points in Google’s AI stack, converting them into reusable modules or formal product feature requests for the Engineering teams.
- Co-build with customer engineering teams to instill Google-grade development best practices, ensuring long-term project success and high end-user adoption.

### Qualifications

### Minimum qualifications:

- Bachelor's degree in Computer Science, Engineering, a related field, or equivalent practical experience.
- 8 years of experience building and shipping production-grade AI-driven solutions to external or internal customers using Python, TypeScript or comparable languages.
- Experience building scalable pipelines for structured, unstructured data, incorporating vector databases and RAG-like architectures to power enterprise-grade AI solutions.
- Experience leading technical discovery sessions with executive stakeholders (C-suite) and engineering teams to define AI and hardware infrastructure requirements.
- Experience architecting scalable AI systems on cloud platforms.

### Preferred qualifications:

- Master’s degree or PhD in AI, Computer Science, or a related technical field.
- Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, or Google’s ADK) and complex patterns like ReAct, self-reflection, and hierarchical delegation.
- Proven experience architecting integrated systems, navigating real-time inference constraints, and implementing model quantization for resource-constrained environments.
- Experience partnering with Higher Education customers, specifically R1 institutions, to drive digital transformation and AI-readiness.
- Knowledge of "LLM-native" metrics (tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.
- Proficiency in Vertex AI Pipelines, Kubeflow, or MLflow to implement CI/CD/CT automation and experimentation.

[View posting at Google](https://www.google.com/about/careers/applications/jobs/results/85626706013889222)

## About Google

Builds global consumer, ads, cloud, developer and AI platforms spanning Search, YouTube, Android, Workspace and Gemini.

Public · 5000+ people

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