AI Solution Architect İstanbul Türkiye Big Data Solutions Management Posted ago

Position: AI Solution Architect İstanbul Türkiye Big Data Solutions Management Posted 2 hours ago
## AI Solution Architectİstanbul, Istanbul, Türkiye##
** Join Us
** At Vodafone, we’re not just shaping the future of connectivity for our customers – we’re shaping the future for everyone who joins our team. When you work with us, you’re part of a global mission to connect people, solve complex challenges, and create a sustainable and more inclusive world. If you want to grow your career whilst finding the perfect balance between work and life, Vodafone offers the opportunities to help you belong and make a real impact.##

** What you’ll do
** We are seeking an experienced AI & Data Architect to design, build, and govern end‐to‐end AI and data solutions leveraging modern lakehouse architectures, technologies, and methodologies. The ideal candidate will play a critical role in defining enterprise‐scale data and AI architectures, enabling advanced analytics, machine learning, and Generative AI (GenAI) initiatives. You will ensure robust data foundations, seamless data and ML pipelines, and high‐performing, scalable AI applications across hybrid environments, including local analytic platforms (Cloudera & Practicus

AI) and cloud ecosystems.  Key Accountabilities  AI Solution Development:  
• Design, develop, and implement end-to-end AI solutions across various business domains.  
• Lead the deployment of AI models, algorithms, and systems in production environments.  
• Collaborate with data scientists to implement generative AI solutions using foundational models like LLMs in local data centers.
Data Architecture and Management:  
• Define efficient data architectures to feed machine learning models and facilitate seamless data sharing across systems.  
• Ensure high data quality, performance, and cost efficiency in operational pipelines.  
• Develop and manage real-time data processing and analytics architectures integrated with business systems.  
• Apply MLOps, Data Ops, and AIOps principles to create sustainable and effective value chain management processes.  
• Stay updated on advancements in AI technologies and apply them to improve business outcomes.  
• Aligns data architecture and technology choices with enterprise data strategy to maximize long-term business value.  
• Establishes AI-ready data foundations that enable advanced analytics and machine learning use cases at scale.  
• Defines real-time and event-driven data architectures that enable timely insights and tight integration with business processes.
Infrastructure and Performance Optimization:  
• Establish robust infrastructures to ensure AI models operate with accurate data, meet SLAs, and deliver high performance.  
• Optimize workflows for stability and efficiency in processing petabyte-scale data in on-premise environments.
Leadership and

Collaboration:

• Provide technical guidance and mentorship to data engineers and scientists.  
• Collaborate with enterprise architects, solution architects, and stakeholders to ensure seamless integration of AI solutions.
Security and Compliance:  
• Implement best practices to protect sensitive data and AI systems while maintaining compliance with industry standards.##
** Who you are
** Bachelor's degree or higher in a technology-related field (e.g., Computer Science, Mathematics, Industrial Engineering, or related quantitative disciplines).Experience &

Skills:

At least 6 years of experience designing, building, and managing large-scale data applications, particularly in Hadoop ecosystems (Cloudera, Spark, Hive/Impala, etc.).  Hands-on experience with AI frameworks and libraries, such as Tensor Flow, PyTorch, and Scikit-learn.  Strong knowledge of GenAI, including foundational models, generative adversarial networks, and reinforcement learning.  Expertise in software development using Python, Java, or Scala (additional languages are a plus).  

Proven experience deploying AI models in production environments.  Proficiency in containerization and orchestration tools like Docker and Kubernetes.  Strong understanding of private and hybrid cloud environments, microservice architectures, and real-time analytics.

Preferred

Skills:

Knowledge of Agile methodologies, including Scrum, Dev Ops, MLOps, and Data Ops. …