Job Summary :
Solution Architect with deep proficient knowledge in Google Cloud Platform (GCP) and AI services to lead the design and deployment of intelligent, scalable, and secure cloud solutions.
Youll play a pivotal role in shaping our cloud and AI strategy, bridging business needs with technical execution and driving innovation across the organization.
Key Responsibilities :
- Architect and implement end-to-end solutions using GCP services, with a focus on AI and machine learning capabilities.
- Collaborate with stakeholders to gather requirements and translate them into scalable, intelligent architectures.
- Lead cloud migration and modernization initiatives, integrating AI-driven components where applicable.
- Design and deploy models using GCP AI tools such as Vertex AI, BigQuery & Custom model development.
- Define best practices for cloud security, scalability, and cost optimization.
- Create architectural diagrams, documentation, and technical roadmaps.
- Provide technical leadership and mentorship to development and data science teams.
- Conduct architecture reviews and ensure alignment with enterprise standards.
- Stay current with GCP updates, AI trends, and emerging technologies.
Required Skills & Qualifications :
Bachelors or masters degree in computer science, Engineering, or related field.7+ years of experience in software development and architecture roles.3+ years of hands-on experience with GCP services (Compute Engine, Cloud Functions, BigQuery, Cloud Storage, etc.)Proven experience with GCP AI / ML services (Vertex AI, AutoML, BigQuery ML, etc.)Strong understanding of cloud-native design, microservices, and container orchestration (Kubernetes, GKE).Experience with CI / CD pipelines and DevOps practices.Excellent communication and stakeholder engagement skills.Ability to balance technical depth with business strategy.Preferred Qualifications :
GCP Professional Cloud Architect or Professional Machine Learning Engineer certification.Experience with hybrid and multi-cloud environments.Familiarity with infrastructure-as-code tools (Terraform, Deployment Manager).Background in data architecture, model lifecycle management, and MLOps.(ref : hirist.tech)