Job Description
The Future is Now. QuantumLeap Systems is pioneering the infrastructure for the next decade. We are seeking a visionary Senior AI Infrastructure Engineer to lead our flagship 2026 Roadmap initiative. If you are passionate about building scalable, high-performance systems that will define the technology of the future, we want to meet you.
In this pivotal role, you will bridge the gap between cutting-edge machine learning research and robust, production-grade engineering. You will be responsible for architecting the core systems that power our next-generation AI solutions, ensuring they are secure, scalable, and future-proof.
Why Join Us?
We offer a competitive salary, equity package, and the opportunity to work on projects that will impact the world for years to come. Work in a dynamic, collaborative environment with industry leaders.
Responsibilities
- Architect High-Performance Systems: Design and implement scalable microservices and infrastructure for large-scale AI model training and inference.
- Lead the 2026 Roadmap: Define technical strategies and roadmaps to transition legacy systems to next-generation architectures.
- Optimize MLOps Pipelines: Streamline the deployment, monitoring, and maintenance of machine learning models using CI/CD and containerization technologies.
- Ensure Security & Compliance: Implement rigorous security protocols to protect sensitive data and ensure adherence to industry standards.
- Collaborate with Cross-Functional Teams: Work closely with data scientists, software engineers, and product managers to translate business requirements into technical solutions.
- Performance Tuning: Identify bottlenecks in our systems and implement optimizations to improve latency and throughput.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
- Experience: 5+ years of professional experience in software engineering, DevOps, or Systems Architecture.
- Programming: Proficiency in Python, Go, or Rust, with a strong understanding of systems programming.
- Cloud Expertise: Deep experience with cloud platforms (AWS, GCP, or Azure) and container orchestration (Kubernetes/Docker).
- AI Knowledge: Strong understanding of machine learning concepts and experience integrating AI models into production environments.
- Strategic Thinking: Ability to anticipate future trends in AI and hardware to build adaptable infrastructure.