Lead GCP Engineer: AI Platforms & Development
New
United StatesFull-TimeLead
Salary122,001 - 191,715 USD per year
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Job Details
- Experience
- 8+ years of software engineering experience
- Required Skills
- PythonGCPGoCI/CDTerraformPrompt EngineeringMLOps
Requirements
- 8+ years of software engineering experience with strong backend development expertise.
- 3+ years of hands-on experience building and deploying solutions on Google Cloud Platform.
- Strong proficiency in Python and/or Go for backend and cloud-native development.
- Deep experience with Gemini models, Vertex AI, prompt engineering, and function calling.
- Experience building or supporting RAG-based architectures and generative AI systems.
- Solid understanding of cloud-native architectures, microservices, and distributed systems.
- Familiarity with CI/CD pipelines and Infrastructure-as-Code tools such as Terraform (preferred).
- Experience with LLM evaluation frameworks, observability, and AI safety practices.
- Google Cloud Professional certifications and experience with Agent Development Kit or Vertex AI Agent Builder are highly desirable.
Responsibilities
- 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 evaluation frameworks.
- Lead the development of innovation lab assets, including accelerators, reusable components, and AI starter kits for enterprise deployment.
- Collaborate across AI, data, and engineering teams to align best practices and ensure consistent implementation of GCP AI architectures.
- Contribute to architectural standards and technical governance for scalable and secure AI platform development.
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