Google Cloud Platform Engineer with GenAI Skills
Experience Required
6 8 years of hands-on experience in Google Cloud Platform (Google Cloud Platform) with strong exposure to cloud migration and modern AI/GenAI technologies.
Role Overview
We are seeking a highly skilled Google Cloud Platform Engineer with expertise in Generative AI to design, develop, and deploy scalable cloud-native solutions. The ideal candidate will have experience in cloud migration, data engineering, AI/ML, and GenAI applications, along with a solid understanding of MLOps/LLMOps and enterprise integrations.
You will work closely with cross-functional teams to deliver AI-driven, data-intensive solutions on Google Cloud Platform that enable business transformation.
Key Responsibilities
Cloud & Architecture
- Design and implement scalable, secure, and highly available cloud-native solutions on Google Cloud Platform.
- Lead and execute cloud migration initiatives (on-premise to Google Cloud Platform / multi-cloud).
- Architect microservices-based solutions using Google Cloud Platform services such as:
- GKE (Google Kubernetes Engine)
- Cloud Run
- App Engine
- Cloud Functions
Data Engineering & Analytics
- Develop, build, and optimize data pipelines using Google Cloud Platform tools like:
- BigQuery
- Dataflow
- Dataproc
- Pub/Sub
- Design and implement ETL/ELT workflows for large-scale data processing.
- Optimize query performance and manage data warehousing solutions on BigQuery.
AI / ML & Generative AI
- Develop and deploy AI/ML and Generative AI solutions, including:
- Chatbots, agents, copilots, and automation tools
- Work with LLMs (Large Language Models) and frameworks like:
- Vertex AI
- LangChain / similar orchestration frameworks
- Fine-tune, evaluate, and deploy models for real-world use cases.
Integration & APIs
- Integrate LLMs with enterprise applications using APIs and microservices.
- Design RESTful and event-driven architectures.
- Enable seamless interaction between AI services and business applications.
MLOps / LLMOps
- Implement end-to-end MLOps / LLMOps pipelines:
- Model training, deployment, monitoring, and retraining
- Use tools like:
- Vertex AI Pipelines
- CI/CD integrations (GitHub Actions, Cloud Build)
- Monitor model performance, drift, and reliability.
Security, Governance & Optimization
- Ensure adherence to cloud security best practices:
- IAM, VPC, encryption, and compliance standards
- Establish data governance frameworks
- Optimize system performance and cost efficiency.
Collaboration & Stakeholder Interaction
- Work closely with:
- Business stakeholders
- Data engineers and scientists
- Platform and DevOps teams
- Translate business requirements into scalable technical solutions.
- Drive AI-led innovation across projects.
Essential Skills
- 6 8 years of experience in Google Cloud Platform (Google Cloud Platform)
- Proven experience in cloud migration projects
- Strong expertise in:
- BigQuery, Dataflow, Dataproc
- ETL/ELT pipeline development
- Hands-on experience with:
- Vertex AI or similar ML platforms
- LLM integration and GenAI frameworks
- Experience in:
- Microservices architecture
- API development and integration
- Knowledge of:
- MLOps / LLMOps practices
- CI/CD pipelines
- Strong understanding of:
- Cloud security and governance
- Proficiency in programming languages such as:
Thanks & Regards
Ajay Pratap Singh
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