12 days ago
Field Solutions Architect GenAI
On Site
Full Time
₹0
Gurgaon, Haryana, India
Job Overview
Job TitleField Solutions Architect GenAI
Job TypeFull Time
CategoryCommerce
Experience5 Years
DegreeMaster
Offered Salary₹0
LocationGurgaon, Haryana, India
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Job Description
About the Role
As a Field Solutions Architect GenAI at Google Cloud, you will bridge the gap between frontier AI products and production-grade solutions, directly working within customer environments to address integration challenges and deployment blockers.
Minimum Qualifications
- Bachelor’s degree in STEM or equivalent practical experience
- 8 years of experience with production-grade AI solutions and Python (L400-level)
- Experience leading technical discovery sessions with executive stakeholders and engineering teams
- Expertise in building full-stack solutions interfacing with enterprise systems
Preferred Qualifications
- Master's degree or PhD in Computer Science, AI, Machine Learning or related field
- Experience in enterprise scale production-grade ML systems and MLOps architecture
- Skilled in resilient data engineering pipelines using BigQuery and Vertex AI
- Knowledge of model governance, monitoring, batch and online serving strategies
- Proficiency in Vertex AI Pipelines, Kubeflow, or MLflow
Responsibilities
- Lead development for AI applications from prototypes to production workflows
- Architect and code integrations between Google AI products and customer infrastructure
- Build high-performance evaluation pipelines and observability frameworks
- Identify and convert field patterns into reusable modules or feature requests
Key skills/competency
- AI solutions
- Python
- Cloud architecture
- Data pipelines
- Enterprise systems
- Production-grade deployment
- MLOps
- API integration
- Observability
- Technical discovery
How to Get Hired at Google
- Research Google Cloud: Study their culture, products, and updates.
- Customize Your Resume: Highlight experience in production-grade AI and cloud platforms.
- Focus on Technical Skills: Emphasize Python, MLOps and API integrations.
- Prepare for Interviews: Understand enterprise system challenges and solutions.
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