#849 - AI Architect

Responsibilities

• Architect Scalable AI Solutions: Design and develop robust, scalable architectures that leverage Generative AI and Python to align with business goals.
• Cross-functional Collaboration: Partner with engineering, product, and business teams to integrate AI capabilities into existing systems and workflows.
• Technical Analysis & Planning: Translate complex business requirements into detailed technical specifications and project plans.
• Mentorship: Guide and mentor junior engineers, fostering growth, innovation, and adherence to best practices in AI development.
• AI Model Development: Oversee the implementation and deployment of AI models and algorithms, ensuring performance, accuracy, and efficiency.
• Tool & Framework Selection: Evaluate and recommend appropriate tools, libraries, and frameworks to enhance development and deployment processes.
• System Monitoring & Optimization: Continuously monitor AI systems in production and implement improvements based on performance metrics.
• Compliance & Standards: Ensure all solutions adhere to relevant industry standards, security protocols, and ethical AI guidelines.
• Continuous Improvement: Lead initiatives for innovation, optimization, and continuous improvement in AI strategies and solutions.
• Stakeholder Engagement: Work closely with business stakeholders to understand needs and deliver impactful, AI-driven solutions.
• Documentation & Enablement: Develop technical documentation, training materials, and internal resources to facilitate adoption and knowledge sharing.
• Industry Awareness: Stay current with emerging trends in AI, Python, and machine learning to continuously enhance organizational capabilities.
• Strategic Impact: Contribute to the companys broader mission by delivering AI solutions with positive societal and business impact.

• +B2 Upper intermediate english. 
• Proven experience in designing and deploying AI systems, with a focus on Generative AI (e.g., LLMs, diffusion models, transformers).
• Proficient in Python and associated AI/ML libraries such as TensorFlow, PyTorch, Hugging Face, scikit-learn, etc.
• Strong analytical and problem-solving skills, with the ability to convert abstract concepts into concrete technical solutions.
• Experience mentoring and leading technical teams on complex AI initiatives.
• Up-to-date knowledge of the AI landscape, including research papers, open-source tools, and industry applications.
• Excellent communication and interpersonal skills, with the ability to explain technical concepts to non-technical stakeholders.
• Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and DevOps tools for model deployment and lifecycle management.