Senior Technical Architect

We are in search of a proficient Senior Technical Architect, responsible for spearheading the creation and deployment of robust, scalable, and secure solutions within cloud, on-premise, and AI-driven environments. The successful candidate will possess extensive knowledge in cloud architecture (AWS, Azure, GCP), on-premise platforms (such as SUSE Rancher), containerization, data engineering, and generative AI technologies. You will have a crucial role in guiding technical strategies, mentoring engineering teams, and adhering to best practices in system design, DevOps, and security measures.

Key responsibilities include:

• Designing and implementing scalable, secure, and resilient cloud-native and on-premise architectures.
• Leading solution architecture utilizing AWS, Azure, GCP, and SUSE Rancher for hybrid cloud setups.
• Developing and scaling microservices architectures with Docker and Kubernetes.
• Promoting the adoption of DevOps and CI/CD pipelines to enhance engineering productivity.
• Architecting and executing data pipelines, ETL workflows, and comprehensive data engineering solutions.
• Leading the integration of machine learning and generative AI models using tools such as TensorFlow, PyTorch, and platforms like OpenAI and Hugging Face Transformers.
• Delivering technical leadership and mentoring across teams to ensure code quality and architectural alignment.
• Collaborating with product, data, and engineering teams to synchronize technical strategies with business objectives.
• Establishing and enforcing security best practices, compliance standards, and risk management protocols.
• Encouraging innovation and strategic foresight to stay ahead of technological trends and future-proofing systems.
• Demonstrating a solid background in designing and supervising large-scale architectures for both cloud and on-prem environments.
• Proficiency in cloud platforms: AWS, Azure, GCP.
• Practical experience with SUSE Rancher or similar on-prem orchestration systems.
• Strong programming capability in Python, particularly for data and ML applications.
• Comprehensive understanding of machine learning and generative AI ecosystems such as OpenAI API, Hugging Face, TensorFlow, and PyTorch.
• Robust experience in data engineering, ETL design, and creating scalable data pipelines.
• In-depth expertise in microservices design, API development, and container orchestration.
• Experience with CI/CD, DevOps tools, and contemporary infrastructure automation.
• Extensive knowledge of cybersecurity principles, identity and access management, and data protection strategies.
• Exemplary problem-solving, communication, and leadership skills.
• Capacity to align technical decisions with overarching business strategies.
• Relevant certifications in AWS, Azure, GCP, or Kubernetes (CKA/CKAD).
• Experience in multi-cloud or hybrid cloud frameworks.
• Background in MLOps and real-time inference systems.
• Acquainted with event-driven architectures and streaming platforms, for instance, Kafka.