AI Practice Architect

Yêu cầu ứng viên Knowledge:• Software Engineering: Expertise in building scalable and robust software applications. Skilled in designing, implementing, and optimizing systems to handle high traffic and large data volumes efficiently.• AI/ML: Deep understanding of large language models (LLMs) like Llama, Mistral and AI/ML frameworks such as TensorFlow, PyTorch, and Scikit-learn. Proficiency in the full AI/ML lifecycle, including data preparation, model training, deployment, and monitoring (e.g., MLOps pipelines). Understanding of AI-driven automation, including intelligent process automation, predictive analytics, and autonomous systems.• Data Engineering: Expertise in building scalable data pipelines and real-time streaming using tools like Apache Kafka, Flink, and Spark. Strong knowledge of data orchestration tools (e.g., Apache Airflow, Prefect) and database optimization (SQL and NoSQL).• Architecture and Design Patterns: Experience with microservices, event-driven systems, and serverless architecture. Deep understanding of automation-friendly architecture frameworks and patterns, such as Infrastructure as Code and self-healing systems.• Security and Compliance: Knowledge of secure AI, automation, and data systems, including data governance, GDPR, and SOC 2. Familiarity with automation for compliance monitoring and reporting.• Emerging Technologies: Awareness of cutting-edge trends in automation, such as hyper-automation and low-code/no-code platforms, and their integration with AI systems.Experience:• Technical Leadership: Over 10 years in software engineering or technology roles, with at least 4 years in leadership positions related to AI and Data Science.• AI/ML and Data Systems: Proven track record of delivering AI/ML-powered solutions, such as intelligent chatbots, fraud detection systems, or workflow optimization. Hands-on experience in building and managing scalable data platforms and predictive analytics pipelines.• Cross-Functional Collaboration: Experience working closely with stakeholders across engineering, data science, operations, and business functions to deliver AI and automation solutions.• Mentorship: Experience guiding engineering teams to adopt best practices in AI-related areas.Competency:• Strategic Thinking: Ability to align AI solutions with organizational goals and long-term strategies.• Systems Thinking: Expertise in designing solutions that seamlessly integrate AI services into ecosystems.• Analytical Skills: Strong ability to solve complex automation and data challenges while ensuring efficiency and scalability.• Leadership and Influence: Proven track record of leading multi-disciplinary teams and influencing stakeholders to adopt AI and automation initiatives.• Agility and Adaptability: Comfortable navigating dynamic technological environments and adapting to emerging trends in Cloud, Automation, AI, and Data.• Execution Excellence: Demonstrated ability to deliver reliable, scalable AI solutions on time and within budget.Personal Attributes:• Visionary: Forward-thinking and able to envision how AI can transform business processes and drive innovation.• Collaborative: Skilled at building relationships across teams to deliver integrated and impactful AI solutions.• Detail-Oriented: Focused on ensuring the quality, reliability, and security of AI and data systems.• Ethical: Committed to the responsible use of AI and automation, ensuring compliance with ethical and regulatory standards.• Continuous Learner: Enthusiastic about exploring advancements in AI, data, and automation technologies and applying them to real-world problems.• Resilient: Able to handle challenges with persistence and adaptability, driving successful outcomes in high-pressure environments.