Job Description
Are you ready to engineer the future?
Apex Horizon Technologies is seeking a visionary Lead AI Architect to spearhead the infrastructure for our 2026 roadmap. We are not just building software for today; we are constructing the resilient, scalable backbone for the next generation of artificial intelligence.
In this pivotal role, you will bridge the gap between cutting-edge machine learning research and robust, production-grade engineering. You will define the architectural standards that allow our AI models to scale effortlessly in a high-demand environment. If you have a passion for solving complex scalability problems and a desire to be at the forefront of technological evolution, we invite you to join our elite team.
Why join us?
- Future-Proofing: Work on projects designed to lead the industry into 2026 and beyond.
- Impact: Your code will power intelligent systems used by millions.
- Culture: A collaborative, diverse environment that values innovation and technical excellence.
Responsibilities
- Architect Future-Ready Systems: Design and implement scalable, fault-tolerant cloud infrastructure specifically optimized for next-generation AI workloads and large language models.
- Performance Optimization: Lead initiatives to reduce inference latency and improve model efficiency, ensuring high throughput under peak loads.
- Cloud Strategy: Drive the migration and management of complex CI/CD pipelines using Kubernetes and containerization technologies.
- Security & Compliance: Implement rigorous security protocols to protect sensitive data and ensure adherence to global standards.
- Technical Leadership: Mentor junior engineers and conduct architecture reviews to ensure code quality and scalability.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- Experience: 7+ years of professional software engineering experience with at least 3 years in Machine Learning Operations (MLOps) or AI Infrastructure.
- Technical Skills: Deep expertise in Python, C++, or Rust; proficiency with major cloud providers (AWS, GCP, or Azure).
- Tools: Strong experience with Docker, Kubernetes, Terraform, and CI/CD tools (Jenkins, GitLab CI).
- Problem Solving: Demonstrated ability to troubleshoot complex distributed systems and optimize resource allocation.