Lead GCP Engineer: AI Platforms & Development
Company: Jobgether
Location: Location not specified (Remote)
Type: Full-time
Remote: Yes
Posted: 2026-06-04
About this role
This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Lead GCP Engineer: AI Platforms & Development in the United States.
This role sits at the core of next-generation AI engineering, focused on building and scaling agentic systems within a Google Cloud environment. You will act as the technical authority for AI-driven backend development, responsible for transforming advanced language models into production-ready, enterprise-grade applications. The position bridges AI research concepts and real-world systems by designing scalable services, APIs, and data pipelines that power intelligent agents. You will work closely with cross-functional teams to ensure seamless integration of AI capabilities into enterprise platforms while defining engineering standards for GCP-based development. This is a highly hands-on role where you will also contribute to innovation through accelerators, reusable assets, and proof-of-concepts. Operating in a collaborative and fast-evolving environment, you will help shape best practices for building secure, scalable, and production-ready AI systems. The role is ideal for an engineer passionate about generative AI, cloud-native architecture, and building impactful AI products at scale.
Accountabilities
- Design, build, and maintain production-grade backend services and APIs that orchestrate AI agent workflows on Google Cloud Platform.
- Develop and optimize prompt engineering strategies, including system instructions, few-shot learning, and Gemini model tuning.
- Lead the productionization of AI prototypes into scalable cloud-native solutions using services such as Cloud Run, GKE, Vertex AI, and Cloud Functions.
- Build integration layers and connectors enabling AI systems to interact with enterprise data sources, vector databases, and Google Cloud data services.
- Establish CI/CD pipelines and MLOps-aligned practices for LLM-based applications, including prompt versioning and evalua...