Forward Deployed Engineer

About the role

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 architecting scalable AI systems on cloud platforms.
• Experience leading technical discovery sessions with executive stakeholders

(C-suite) and engineering teams to define AI and hardware infrastructure

requirements.

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.

• Proficiency in Vertex AI Pipelines, Kubeflow, or MLflow to implement CI/CD/CT

automation and experimentation.

• Knowledge of "LLM-native" metrics (tokens/sec, cost-per-request) and

techniques for optimizing state management and granular tracing.

• Designing resilient data engineering pipelines using BigQuery and VertexAI

for enterprise-scale analytics.

ABOUT THE JOB:

The Google Public Sector Forward Deployed Engineering (GPS FDE) team 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. We resolve

complex integration, data sovereignty, and security issues within strict

compliance frameworks, utilizing talent with TS/SCI clearances. 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.

As a Forward Deployed Engineer (FDE) in Google Public Sector (GPS), you will be

an embedded builder who bridges the gap between frontier AI products and

production-grade reality within customers. Unlike traditional advisory roles,

you will function as a moving beyond high-level architecture to code, debug, and

jointly ship bespoke agentic solutions directly within the customer’s

environment.

This role is designed for high-agency engineers with a founder’s mindset. You

will manage blockers to production including solving the integration

complexities, data readiness issues, and state-management issues that prevent AI

from reaching enterprise-grade maturity. By embedding with accounts, you serve a

dual purpose: providing "white glove" deployment of complex AI systems and

acting as a critical feedback loop, transforming real-world field insights into

Google Cloud’s future product roadmap.

This role will be focusing on the State and Local Government Market.

Google Public Sector

[https://about.google/intl/ALL_us/public-sector/#:~:text=We're%20committed%20to%20advancing,%2C%20research%2C%20and%20edtech%20companies.]

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

[https://www.google.com/about/careers/applications/benefits/].

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 return on investment (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.