Gen AI Architect
Gen AI Architect
Posted on :
20-12-2024
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1 Vacancy
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Job Description
Title: AI Architect (Google)
Seniority: Senior
Description & Requirements
Position Summary
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 GPT4o 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 containerbased 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 GCPs 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 cloudnative 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 GCPs cloudnative/12factor characteristics.
Promote the adoption of GCP GenAI technologies within cloudnative 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 cloudnative applications and architectures.
Conduct workshops briefings and strategic dialogues to educate clients on AI benefits and applications building strong trustbased relationships.
Act as a trusted advisor contributing to technical projects (PoCs and MVPs) with a focus on technical excellence and ontime 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 MultiCustomer Management
Engage with multiple customers simultaneously providing highimpact 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 handson 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 GPT4o Gemma) NLP techniques Vector Databases FineTuning and GCP Vertex AI components.
Experience with GCPs 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 finetuning 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 fastpaced environment using the latest technologies and passionate about dynamic and highenergy 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).
Mohsen s 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 GCPbased 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 problemsolving abilities and effective crosscultural collaboration.
Adept at driving organizational change and fostering a culture of innovation.
mlops,automl,artificial intelligence,google,cloud professional certifications,innovation culture,deep learning frameworks (tensorflow, pytorch),problem-solving abilities,google cloud storage,nlp techniques,pytorch,tensorflow,innovation and emerging technology trends,big query,gcp,google kubernetes engine (gke),google cloud platform (gcp),big data,ai/cloud provider certifications,cloud,ai ethics and bias mitigation,google cloud platform,organizational change management,containerization,data preprocessing,distributed systems,spring,genai models (e.g., gemini, gpt-4o, gemma),strategic ai vision and road mapping,cross-cultural collaboration,ai architecture design,communication skills,google cloud,feature engineering,go (golang),machine learning algorithms,machine learning,fast-paced environment,google cloud dataflow,java,python,kubernetes,cloud architecture design,serverless computing,leadership skills,nlp,java (and/or golang)
Employment Type
Full Time
Key Skills
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