AI Architect (Google)

The Senior AI Architect is responsible for designing and implementing advanced AI and cloud architectures, with a strong emphasis on integrating generative AI technologies using Google Cloud Platform (GCP). This role requires a broad understanding of AI and cloud platforms, along with the ability to engage with customers on a variety of architectural topics in both cloud and data center environments. The ideal candidate is passionate about GenAI and AI technologies, stays current with industry trends, and drives innovation within the organization and for clients. As a senior leader, you will interact frequently with customers, provide expert opinions, and contribute to strategic vision.

Key Responsibilities
Technical & Engineering Leadership
Design and implement AI and cloud architectures, integrating GCP GenAI technologies like Gemini, GPT-4o, and Gemma to enhance functionality and scalability.
Lead architectural discussions with clients, providing expert guidance on best practices for AI and cloud integration using GCP.
Ensure solutions align with microservice and container-based environments across public, private, and hybrid clouds using Google Kubernetes Engine (GKE).
Contribute to thought leadership in the Cloud Native domain with a strong understanding of
GCP technologies.
Collaborate on technical projects with global partners, leveraging GCP's extensive capabilities.

Service Delivery & Innovation

Develop GenAI solutions from ideation to MVP using GCP services such as Vertex AI, ensuring high performance and reliability within cloud-native frameworks.
Optimize AI and cloud architectures on GCP to meet client requirements, balancing efficiency and effectiveness.
Evaluate existing complex solutions and recommend architectural improvements to transform applications with GCP's cloud-native/12-factor characteristics.
Promote the adoption of GCP GenAI technologies within cloud-native projects, driving initiatives that push the boundaries of AI integration in GCP services.

Thought Leadership and Client Engagement
Provide architectural guidance to clients on incorporating GenAI and machine learning into their GCP cloud-native applications and architectures.
Conduct workshops, briefings, and strategic dialogues to educate clients on AI benefits and applications, building strong, trust-based relationships.
Act as a trusted advisor, contributing to technical projects (PoCs and MVPs) with a focus on technical excellence and on-time delivery.
Author whitepapers, blogs, and speak at industry events, maintaining a visible presence as a thought leader in AI and cloud architecture.
Create and record videos to share insights and opinions on AI and cloud technologies, enhancing industry leadership.

Collaboration and Multi-Customer Management
Engage with multiple customers simultaneously, providing high-impact architectural consultations and fostering strong relationships.
Work closely with internal teams and global partners to ensure seamless collaboration and knowledge sharing across projects.
Maintain a hands-on technical credibility, staying ahead of industry trends and mentoring others in the organization.

Mandatory Skills & Experience

Experience: 8+ years in cloud and AI architecture design, 5+ years in software development.
Technologies: Proficiency in Python, Java (and/or Golang), and Spring; expertise in Google Cloud Platform; Google Kubernetes Engine (GKE) and containerization.
AI Expertise: Advanced machine learning algorithms, GenAI models (e.g., Gemini, GPT-4o, Gemma), NLP techniques, Vector Databases, Fine-Tuning and GCP Vertex AI components.

Experience with GCP's AI tools such as Vertex AI, TensorFlow, and AutoML is required
Big Data: Experience with Big Query, Google Cloud Dataflow, and Google Cloud Storage.

Desired Skills & Experience
Deep knowledge of machine learning operations (MLOps) and experience in deploying, monitoring, and maintaining AI models in production environments on GCP.
Proficiency in data engineering for AI, including data preprocessing, feature engineering, and pipeline creation using Google Cloud Dataflow and BigQuery ML.
Expertise in AI model fine-tuning and evaluation, with a focus on improving performance for specialized tasks.
Knowledgeable about AI ethics and bias mitigation, with experience in implementing strategies to ensure fair and unbiased AI solutions.
Serverless Computing and Distributed Systems on GCP.
Deep Learning Frameworks (TensorFlow, PyTorch) integrated with GCP AI Platform.
Innovation and Emerging Technology Trends.
Strategic AI Vision and Road mapping.
Enthusiastic about working in a fast-paced environment using the latest technologies, and passionate about dynamic and high-energy Labs atmosphere.

Verifiable Certification

At least two recognized cloud professional certifications: one must be from Google Cloud Platform (e.g., Google Professional Cloud Architect), and another can be from Google or a relevant AI/cloud provider (e.g., Microsoft Azure, AWS).
Mohsens suggestion:
At least two recognized cloud professional certifications: one must be from Google Cloud Platform (e.g., Google Professional Cloud Architect) or demonstrated experience running GCP-based AI projects in production. Another certification can be from Google or a relevant AI/cloud provider (e.g., Microsoft Azure, AWS).

Soft Skills and Behavioral Competencies
Exemplary communication and leadership skills, capable of inspiring teams and making strategic decisions that align with business goals.
Demonstrates a strong customer orientation, innovative problem-solving abilities, and effective cross-cultural collaboration.
Adept at driving organizational change and fostering a culture of innovation.

Skills : - cloud, AI architecture design, Java, Golang, Spring, Google Cloud Platform, Google Kubernetes Engine,GKE, Advanced machine learning algorithms, GenAI models (e.g., Gemini, GPT-4o, Gemma), NLP techniques, Vector Databases, Fine-Tuning and GCP Vertex AI components , Big Query, Google Cloud Dataflow, and Google Cloud Storage , machine learning operations (MLOps) , TensorFlow, PyTorch