Forward Deployed Engineer IV, Applied AI, Google Cloud

Google; Chicago (IL); On-site; USD 207,000 - 300,000; Full time

Benefits offered by this job

Health insurance

401(k) with company match

Paid time off 20 days/year

Sick time 40 hours/year

Job summary

Google is seeking a Forward Deployed Engineer IV in Applied AI within Google Cloud. You will lead the end-to-end engineering lifecycle for conversational AI pilots, turning rapid prototypes into production-grade solutions and partnering with enterprise customers at their sites.

This high-travel role emphasizes AI, cloud, and secure deployments across client environments. You will work with DeepMind minds and Google’s Vertex AI portfolio, driving customer success and delivering scalable AI

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 deploying resources via Terraform or similar tools to automate the setup of agents, functions, or networking.
• Experience building full-stack applications that interact with enterprise IT infrastructures and developing external customer projects.
• Experience architecting AI systems on cloud platforms (e.g., Google Cloud Platform (GCP)).

Responsibilities

• Serve as the lead developer for conversational AI and customer experience 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 conversational flows that are functional, and optimized for the connective tissue between Google’s conversational AI products and customers’ live infrastructure, including APIs, legacy data silos, and security perimeters.
• Build high-performance evaluation pipelines and observability frameworks to optimize agentic workloads, focusing on reasoning loops, tool selection, and reducing latency while maintaining production-grade security and networking.
• Identify repeatable field patterns and technical friction points in Google’s Applied Artificial Intelligence (AAI) stack, converting them into reusable modules or product feature requests for Engineering teams.
• Co-build with customer engineering teams to instill Google-grade development best practices, ensuring project success and end-user adoption.

Skills

Python

Terraform

Full-stack development

Cloud AI architecture

AI systems

Education

Bachelor's degree in Engineering or Computer Science

Master's or PhD in AI/CS (preferred)

Tools

Job description

Forward Deployed Engineer IV, Applied AI, Google Cloud

In most instances, this position requires in-person interviews as part of the hiring process.

The application window will be open until at least September 29, 2026. This opportunity will remain online based on business needs which may be before or after the specified date.

Applicants in the County of Los Angeles: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.

This role may also be located in our Playa Vista, CA campus.

Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.

In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees.

Benefits for this role include:

• Health, dental, vision, life, disability insurance
• Retirement Benefits: 401(k) with company match
• Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
• Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
• Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
• Baby Bonding Leave: 18 weeks
• Holidays: 13 paid days per year

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: San Francisco, CA, USA; Atlanta, GA, USA; Boulder, CO, USA; Chicago, IL, USA; Addison, TX, USA; Irvine, CA, USA; Los Angeles, CA, USA; San Diego, CA, USA; Seattle, WA, USA; Sunnyvale, CA, USA; Austin, TX, USA.

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 deploying resources via Terraform or similar tools to automate the setup of agents, functions, or networking.
• Experience building full-stack applications that interact with enterprise IT infrastructures and developing external customer projects.
• Experience architecting AI systems on cloud platforms (e.g., Google Clloud Platform (GCP)).

Preferred qualifications

• Master’s degree or PhD in AI, Computer Science, or a related technical field.
• Experience implementing multi-agent systems using frameworks like ReAct and self-reflection.
• Experience debugging agent logic and optimizing tool selection, including tracing conversation identifications (IDs) across microservices to identify and resolve failures in real-time.
• Experience connecting agents to enterprise knowledge bases and optimizing retrieval-augmented Generation (RAG) chunking to prevent hallucinations.
• Track record of troubleshooting live, high-traffic systems during critical windows.
• Ability to travel up to 50% of the time.

About the job

As a Forward Deployed Engineer (FDE) in Applied AI, you will be the Agent Engineer and the primary driver for our customers' most critical AI initiatives. You will take initial conversational prototypes and transform them into production-ready solutions, owning the end-to-end engineering lifecycle, including the transition from art of the possible to real-world business value and scalable, secure AI systems. This is a high-travel, role focused on leading technical delivery for conversational AI pilots and establishing the first customer user journeys (CUJs) for our largest customers at their sites. You will have an understanding of software engineering, Machine Learning operations, and cloud infrastructure. It's an exciting time to join Google Cloud’s Go-To-Market team, leading the AI revolution for businesses worldwide. You’ll excel by leveraging Google's brand credibility—a legacy built on inventing foundational technologies and proven at scale. We’ll provide you with the world's most advanced AI portfolio, including frontier Gemini models, and the complete Vertex AI platform, helping you to solve business problems. We’re a collaborative culture providing direct access to DeepMind's engineering and research minds, empowering you to solve customer challenges. Join us to be the catalyst for our mission, drive customer success, and define the new cloud era—the market is yours. 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

Responsibilities

• Serve as the lead developer for conversational AI and customer experience 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 conversational flows that are functional, and optimized for the connective tissue between Google’s conversational AI products and customers’ live infrastructure, including APIs, legacy data silos, and security perimeters.
• Build high-performance evaluation pipelines and observability frameworks to optimize agentic workloads, focusing on reasoning loops, tool selection, and reducing latency while maintaining production-grade security and networking.
• Identify repeatable field patterns and technical friction points in Google’s Applied Artificial Intelligence (AAI) stack, converting them into reusable modules or product feature requests for Engineering teams.
• Co-build with customer engineering teams to instill Google-grade development best practices, ensuring project success and end-user adoption.