Job Description
Welcome to 2026. We are not just building the future; we are defining it. As a leading pioneer in next-generation predictive intelligence and autonomous systems, we are looking for a visionary Senior AI Systems Architect to lead our core infrastructure initiatives.
In this role, you will bridge the gap between theoretical AI research and scalable production systems. You will design robust architectures that can handle billions of data points in real-time, ensuring our solutions remain at the cutting edge of technology.
If you are passionate about solving complex problems and want to leave a legacy in the tech world, we want to meet you.
Responsibilities
- Architect Design: Design and implement scalable, high-performance AI systems and machine learning pipelines that align with our long-term strategic vision.
- System Optimization: Analyze and optimize existing systems for performance, latency, and cost-efficiency, utilizing cloud-native technologies.
- Technical Leadership: Provide technical guidance and mentorship to junior engineers and data scientists, fostering a culture of innovation and best practices.
- Model Deployment: Oversee the end-to-end deployment of AI models, ensuring seamless integration with our microservices architecture.
- Collaboration: Partner with cross-functional teams, including product managers, researchers, and security experts, to deliver high-quality software solutions.
- Research & Development: Stay abreast of the latest advancements in AI, ML, and distributed systems to drive continuous improvement within the organization.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- Experience: 7+ years of experience in software engineering, with at least 3 years focused on AI/ML architecture and system design.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or similar deep learning frameworks. Strong understanding of distributed systems, microservices, and containerization (Docker, Kubernetes).
- Cloud Expertise: Extensive experience with cloud platforms (AWS, GCP, or Azure).
- Problem Solving: Exceptional ability to troubleshoot complex technical issues and make data-driven architectural decisions.
- Communication: Excellent verbal and written communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.