Job Description
Are you ready to architect the future?
Quantum Horizon Technologies is seeking a visionary Senior AI Systems Architect to spearhead our next-generation infrastructure for 2026 and beyond. We are building the backbone of tomorrow's intelligence, and we need a leader who thrives in ambiguity and defines the path forward.
In this role, you will bridge the gap between cutting-edge machine learning research and scalable production systems. You will design resilient, high-performance architectures capable of handling petabyte-scale data streams while ensuring ethical AI deployment.
Why join us?
- Work on projects that redefine the boundaries of human-computer interaction.
- Competitive compensation package including equity and performance bonuses.
- Access to state-of-the-art hardware and cloud environments.
If you are passionate about the convergence of Artificial Intelligence, Distributed Systems, and Ethical Computing, we want to hear from you.
Responsibilities
- Design and deploy scalable AI infrastructure pipelines for real-time processing and predictive analytics.
- Lead a team of brilliant engineers in optimizing neural network models for efficiency and accuracy.
- Define architectural standards for cloud-native AI solutions, ensuring security and compliance.
- Collaborate with product managers to translate complex AI capabilities into user-centric features.
- Conduct code reviews and mentor junior developers on best practices in systems design.
- Research emerging technologies (e.g., Quantum Computing interfaces) to integrate into our roadmap.
Qualifications
- 10+ years of experience in software engineering, with at least 5 years in AI/ML systems architecture.
- Deep expertise in Python, C++, and distributed systems (Kubernetes, Docker).
- Proven track record of deploying machine learning models in production environments at scale.
- Strong understanding of data structures, algorithms, and complexity theory.
- Excellent communication skills, with the ability to articulate technical concepts to non-technical stakeholders.
- Master’s degree in Computer Science, Engineering, or a related field is preferred.