Job Description
We are pioneering the technological landscape of 2026. Apex Horizon Technologies is seeking a visionary 2026 AI Systems Architect to lead our next-generation research division. You will be at the forefront of defining the infrastructure that powers the future of artificial intelligence, merging deep learning with quantum-ready architectures.
In this role, you will bridge the gap between theoretical AI research and scalable, production-grade software engineering. You will define the architectural standards that our global teams will follow to build the intelligent systems of tomorrow. If you are driven by the challenge of solving complex problems and shaping the future of tech, we want to hear from you.
Responsibilities
- Architect Next-Gen AI Infrastructure: Design and implement scalable, high-performance systems capable of handling the computational demands of 2026.
- Lead Model Deployment: Oversee the transition from research prototypes to robust, deployed machine learning models in production environments.
- Optimize Neural Architectures: Continuously improve model efficiency, latency, and accuracy using cutting-edge optimization techniques.
- Collaborate on Cross-Functional Teams: Work closely with data scientists, software engineers, and product managers to align technical roadmaps with business goals.
- Establish Best Practices: Define coding standards, architectural patterns, and CI/CD pipelines for AI workloads.
- Drive Innovation: Stay ahead of the curve on emerging technologies, including Quantum AI, Edge Computing, and Large Language Models.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Artificial Intelligence, or a related technical field.
- Experience: Minimum of 8+ years of experience in software engineering, with at least 5 years specifically in AI/ML systems architecture.
- Technical Proficiency: Deep expertise in Python, C++, and modern frameworks such as PyTorch, TensorFlow, or JAX.
- Cloud Mastery: Proven track record of designing systems on major cloud platforms (AWS, GCP, or Azure).
- Distributed Systems: Strong understanding of distributed computing, containerization (Docker/Kubernetes), and microservices.
- Problem Solving: Demonstrated ability to troubleshoot complex, large-scale system issues under pressure.