Job Description
Are you ready to architect the infrastructure for tomorrow?
Apex Future Systems is seeking a visionary Senior AI & Quantum Readiness Engineer to lead our mission in building scalable, high-performance solutions for the 2026 landscape. We are not just building software; we are engineering the future of computing. In this pivotal role, you will bridge the gap between cutting-edge Artificial Intelligence and emerging quantum computing technologies, ensuring our platforms are robust, secure, and future-proof.
Why join us?
- Work on projects that define the next decade of technology.
- Competitive compensation and equity package.
- Flexible remote-first culture with state-of-the-art equipment.
Responsibilities
- Architect Future-Proof Infrastructure: Design and implement scalable cloud-native architectures (AWS/GCP) optimized for both classical AI workloads and quantum-ready environments.
- System Optimization: Oversee the deployment and scaling of high-performance GPU clusters and HPC (High-Performance Computing) systems.
- MLOps Integration: Develop and maintain CI/CD pipelines and MLOps frameworks to streamline model training and deployment processes.
- Cybersecurity Leadership: Implement zero-trust security protocols and encryption standards to protect sensitive AI data and proprietary algorithms.
- Technical Leadership: Mentor junior engineers and collaborate with data scientists to translate complex research into production-ready infrastructure.
- Performance Monitoring: Utilize advanced monitoring tools to ensure system availability, latency optimization, and resource efficiency.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related technical field.
- Experience: 7+ years of experience in software engineering, DevOps, or system architecture.
- Programming: Proficiency in Python, Go, or Rust with deep experience in containerization technologies (Docker, Kubernetes).
- Cloud Expertise: Strong hands-on experience with major cloud providers (AWS, GCP, or Azure).
- AI Knowledge: Solid understanding of Machine Learning concepts, neural networks, and data pipelines.
- Problem Solving: Demonstrated ability to troubleshoot complex distributed systems and optimize performance under load.