Job Description
We are NextGen 2026, a pioneering force in the future of artificial intelligence and predictive computing. As we accelerate our roadmap towards the technological milestones of 2026, we are seeking a visionary Senior AI Architect to lead our infrastructure and model deployment strategies. If you are passionate about building scalable, high-performance systems that define the next era of technology, we want to hear from you.
In this role, you will be at the intersection of research and production engineering, ensuring our AI models are not only state-of-the-art but also robust, secure, and ready for global scale.
Responsibilities
- Architectural Leadership: Design and oversee the end-to-end architecture of large-scale AI and machine learning systems, ensuring scalability, reliability, and performance.
- Model Deployment: Lead the deployment of advanced machine learning models into production environments, optimizing inference latency and resource utilization.
- Technical Strategy: Define the technical roadmap for AI infrastructure, evaluating new tools, frameworks, and hardware accelerators to stay ahead of industry trends.
- Cross-Functional Collaboration: Work closely with data scientists, software engineers, and product managers to translate complex research concepts into practical, high-impact solutions.
- Code Quality & Mentorship: Establish coding standards and best practices for the engineering team, conducting code reviews and mentoring junior developers to foster a culture of excellence.
- Performance Optimization: Continuously monitor system health and performance, implementing aggressive optimizations to handle increasing data loads and user traffic.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field.
- Experience: 7+ years of professional software engineering experience, with at least 3-5 years specifically focused on AI/ML systems architecture.
- Technical Skills: Deep expertise in Python, TensorFlow, PyTorch, or similar deep learning frameworks. Proficiency in distributed systems and cloud platforms (AWS, GCP, or Azure).
- Problem Solving: Strong analytical skills with a proven track record of solving complex technical challenges in high-pressure environments.
- Communication: Excellent verbal and written communication skills, capable of articulating technical concepts to both technical and non-technical stakeholders.
- Innovation: A forward-thinking mindset with a genuine interest in emerging technologies and the future of AI.