Ads Product Deployment Engineer & Solutions Lead

Google; New York (NY); Hybrid; USD 152,000 - 221,000; Full time

Job summary

Google's gTech Ads Product Deployment Engineering Team seeks a technically adept professional to bridge customer needs and engineering capabilities. You will turn requirements into scalable product strategies and high-quality specs, supporting top enterprise advertising clients.

You will translate customer needs into architectures, draft clear BRD/PRD, and guide handovers to Engineering while addressing gaps and edge cases with a trusted advisory approach.

Qualifications

• Bachelor’s degree in Engineering, CS, or related field, or equivalent practical experience.
• 5 years troubleshooting technical issues for partners or customers.
• 5 years building POC using web scripting (JS, Python) and SQL databases.
• Experience in system design or reading code (Java, C++, Python).
• Preferred: Master’s degree in a technical field.

Responsibilities

• Advise on maximizing complex product adoption with scalable solutions and last-mile customization.
• Translate complex customer requirements into clear system architectures and specs.
• Lead hand-overs to Engineering by authoring BRD and PRD aligned with roadmap.
• Identify product gaps and provide direct feedback to Ads Solution Engineering.
• Provide technical-product oversight during implementation ensuring alignment with strategy.

Skills

Troubleshooting

POC development

Web scripting

SQL databases

Code reading / design

Education

Bachelor's degree or equivalent

Master's degree in technical field

Tools

Java

Python

SQL

Job description

Google's gTech Ads Product Deployment Engineering Team seeks a technically adept professional to bridge customer needs and engineering capabilities. You will turn requirements into scalable product strategies and high-quality specs, supporting top enterprise advertising clients.

You will translate customer needs into architectures, draft clear BRD/PRD, and guide handovers to Engineering while addressing gaps and edge cases with a trusted advisory approach.