Job Description
We are seeking a visionary Senior AI Infrastructure Architect to lead our Project 2026, a groundbreaking initiative aimed at defining the standards for Artificial General Intelligence (AGI) in the coming decade. At Apex Horizon Labs, we are not just building software; we are architecting the future of human-machine symbiosis. This is a unique opportunity to work at the bleeding edge of technology, bridging the gap between quantum computing capabilities and neural network architectures.
You will be responsible for designing resilient, scalable systems that can process petabytes of real-time data while maintaining sub-millisecond latency. If you are passionate about pushing the boundaries of what is possible and thrive in a fast-paced, high-stakes environment, we want to meet you.
Responsibilities
- Architectural Leadership: Define and implement the core infrastructure strategy for Project 2026, ensuring high availability and fault tolerance across global data centers.
- System Optimization: Spearhead research and implementation of advanced caching strategies and edge computing solutions to minimize latency in real-time AI inference.
- Cross-Functional Collaboration: Work closely with quantum physicists and data scientists to integrate novel algorithms into our production pipeline.
- Code Quality: Establish and enforce rigorous coding standards and architectural patterns to ensure maintainability and scalability.
- Mentorship: Guide a team of junior engineers and senior developers, fostering a culture of continuous learning and innovation.
- Security & Compliance: Oversee security protocols to protect sensitive neural network weights and proprietary data assets.
Qualifications
- Experience: 7+ years of experience in software engineering, with at least 3 years in a lead architect role specifically within AI/ML infrastructure.
- Technical Stack: Deep expertise in Python, C++, and Rust; proficiency with Kubernetes, Docker, and distributed systems.
- AI Knowledge: Solid understanding of transformer models, large language models (LLMs), and reinforcement learning environments.
- Education: Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- Soft Skills: Exceptional problem-solving abilities and excellent verbal and written communication skills.