Forward Deployed Engineer IV, GenAI, Google Public Sector

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

Job summary

Google Public Sector, GPS FDE, is seeking engineers to rapidly deploy secure AI solutions across Federal and SLED environments. You will help deploy production-grade, agentic workflows and integration layers with customer infrastructure, APIs, and data perimeters.

As part of a fast-moving squad, you will contribute to the design and implementation of scalable, compliant AI systems, balancing performance with security and governance requirements across mission-critical operations.

Qualifications

• Bachelor's degree in Engineering, Computer Science, a related field, or equivalent practical experience.
• 8 years of experience with software development using Python or similar coding languages.
• Experience building pipelines for structured and unstructured data using both vector databases and RAG-like architectures to power enterprise AI solutions.
• Experience architecting AI systems on cloud platforms (e.g., Google Cloud Platform (GCP)).
• Experience leading technical discovery sessions with customers.
• Must possess an active Top Secret/SCI security clearance.

Responsibilities

• Serve as a developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, model context protocol (MCP) servers) that drive measurable return on investment.
• 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 rigorous 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 development

Technical leadership

Discovery sessions

Education

Bachelor's degree in Engineering, Computer Science, a related field, or equivalent practical experience

Tools

GCP

BigQuery

Vertex AI Pipelines

Kubeflow

MLflow

Job description

MINIMUM QUALIFICATIONS

• Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
• 8 years of experience with software development using Python or similar coding languages.
• Experience building pipelines for structured and unstructured data using both vector databases and RAG-like architectures to power enterprise AI solutions.
• Experience architecting AI systems on cloud platforms (e.g., Google Cloud Platform (GCP)).
• Experience leading technical discovery sessions with customers.
• Must possess an active Top Secret/SCI security clearance.

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, ADK) and complex patterns (e.g., ReAct, self-reflection, hierarchical delegation).
• Proven experience architecting integrated systems, navigating real-time inference constraints, and implementing model quantization for resource-constrained environments.
• Knowledge of Large Language Model (LLM) native metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.
• Proficiency in Vertex AI Pipelines, Kubeflow, or MLflow to implement robust CI/CD/CT automation and experimentation.
• 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 direct "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 challenges within strict compliance frameworks. 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

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

Quick note: 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, model context protocol (MCP) servers) that drive measurable return on investment.
• 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 rigorous 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.