Overview
Skills
Job Details
Job Title: Google Cloud Platform Engineer (DevOps, LLM/AI, Data Engineering)
Location: Remote (USA)
Job Type: C2C / Contract
Duration: 12 Months (with possible extension)
Experience : 10+ years
Must have Telecom Domain Exp
Certification:- Google Cloud Platform (Google Cloud Platform)
Job Overview:
We are seeking a highly skilled Google Cloud Platform Engineer with strong expertise in DevOps, Large Language Models (LLMs), Artificial Intelligence, and Data Engineering. The ideal candidate will design, develop, and optimize cloud-native solutions leveraging Google Cloud Platform services, modern DevOps practices, and AI/ML technologies to support scalable, data-driven business applications.
Key Responsibilities:
- Design, implement, and manage scalable solutions on Google Cloud Platform (Google Cloud Platform).
- Collaborate with cross-functional teams to integrate LLM/AI models into enterprise applications.
- Build and maintain CI/CD pipelines, automate deployments, and ensure high availability.
- Develop and optimize data pipelines for ingestion, transformation, and analytics.
- Work closely with Data Scientists and ML Engineers to deploy and monitor ML/LLM models in production.
- Implement MLOps best practices for AI/ML lifecycle management.
- Monitor system performance, security, and compliance across cloud infrastructure.
- Troubleshoot and resolve issues related to Google Cloud Platform services, DevOps pipelines, and AI deployments.
Required Skills & Qualifications:
- Overall 10+ with 5+ years of hands-on experience as a Cloud/DevOps/Data Engineer.
- Strong expertise in Google Cloud Platform (BigQuery, Dataflow, Vertex AI, Pub/Sub, Cloud Run, etc.).
- Experience with LLMs (OpenAI, Anthropic, Google Gemini, or similar) and integrating AI/ML models into applications.
- Solid background in DevOps (Terraform, Kubernetes, Docker, Jenkins, GitOps, etc.).
- Proficiency in Python, Java, or Go for automation and AI-related tasks.
- Experience with Data Engineering (ETL, data lakes, real-time streaming, SQL/NoSQL databases).
- Knowledge of MLOps frameworks and model deployment pipelines.
- Strong problem-solving skills and ability to work independently in a remote environment.
Preferred Qualifications:
- Google Cloud Platform Professional Certifications (Cloud Architect, Data Engineer, or ML Engineer).
- Experience in Generative AI, NLP, and fine-tuning LLMs.
- Familiarity with data security, governance, and compliance in cloud environments.