Job Description
Are you ready to architect the infrastructure for the next generation of intelligence? Horizon AI Solutions is seeking a visionary Principal AI Architect to lead our strategic roadmap for 2026 and beyond. In this pivotal role, you will define the architectural vision for our next-generation artificial intelligence platforms, ensuring scalability, security, and performance in a rapidly evolving landscape.
We are not just building software; we are shaping the future. You will work closely with cross-functional teams to integrate cutting-edge machine learning models with robust cloud infrastructure. If you are passionate about solving complex problems and have a deep understanding of AI system design, we want to hear from you.
Why Join Us?
• Work on projects that define the industry standards for 2026.
• Competitive compensation package and equity opportunities.
• Flexible remote-first culture with state-of-the-art equipment.
Responsibilities
- Define and articulate the long-term technical vision and architecture for AI systems, specifically targeting deployment and optimization by 2026.
- Lead the design and implementation of scalable, distributed machine learning pipelines and data architectures.
- Collaborate with product management and engineering teams to translate business requirements into technical blueprints.
- Oversee the integration of emerging technologies, including federated learning and edge computing, into our core platform.
- Mentor senior engineers and architects, fostering a culture of technical excellence and innovation.
- Conduct rigorous code reviews and architectural assessments to ensure system integrity and scalability.
- Stay ahead of industry trends to ensure our architecture remains future-proof and competitive.
Qualifications
- Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- 10+ years of experience in software engineering, with at least 5 years specifically in AI/ML architecture and system design.
- Deep expertise in Python, TensorFlow, PyTorch, or similar deep learning frameworks.
- Strong proficiency in cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Proven track record of leading high-impact technical projects from conception to deployment.
- Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
- Experience with MLOps and DevOps practices to streamline the machine learning lifecycle.