Forward Deployed Engineer, Higher Education, Google Public Sector

Socket.dev; Sunnyvale (CA); On-site; USD 207,000 - 300,000; Full time

Job summary

Google GPS FDE team is recruiting a senior engineer to design and deploy production-grade AI solutions. You will translate rapid prototypes into scalable agentic workflows, including multi-agent systems and MCP servers, delivering measurable ROI for public sector customers.

You will connect Google AI products with customer live infrastructure, APIs, data silos, and security perimeters, while collaborating with executive stakeholders and engineering teams to define requirements and ensure

Qualifications

• Bachelor's degree in CS/engineering or equivalent practical experience.
• 8+ years building AI-driven production systems using Python/TypeScript.
• Experience with scalable data pipelines, vector databases, and RAG-like architectures.
• Experience leading executive and engineering discussions to define infrastructure requirements.
• Experience architecting scalable AI systems on cloud platforms.

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.

Skills

Python

TypeScript

AI systems

Data pipelines

Cloud platforms

Executive alignment

Education

Bachelor's degree in CS/Eng

Master's/PhD in AI

Tools

LangGraph

CrewAI

Google ADK

Vertex AI Pipelines

Kubeflow

MLflow

BigQuery

VertexAI

Job description

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.


• Proficiency in Vertex AI Pipelines, Kubeflow, or MLflow to implement robust
  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 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 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.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
nneeds 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 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.