Job Description
We are looking for a visionary Senior AI Infrastructure Architect to build the backbone of tomorrow's generative intelligence. At Lumina Horizon, we are not just adapting to the future; we are defining it. In 2026, the gap between raw compute power and intelligent application is closing, and we need a technical leader to bridge that gap.
The Role:
You will be responsible for designing, deploying, and maintaining the robust cloud infrastructure that powers our next-generation Large Language Models (LLMs). You will work at the intersection of software engineering, data science, and DevOps to ensure our platforms are scalable, secure, and high-performance.
Why Join Us?
- Be part of a team that is redefining the boundaries of artificial intelligence.
- Competitive compensation package and equity options.
- Flexible work environment in the heart of San Francisco's innovation district.
Responsibilities
- Architecture Design: Design and implement scalable, fault-tolerant distributed systems for high-volume AI workloads, utilizing microservices and containerization technologies.
- MLOps Implementation: Establish and maintain CI/CD pipelines for machine learning models, ensuring rapid deployment and seamless integration into production environments.
- Cost Optimization: Continuously analyze infrastructure usage and implement strategies to optimize cloud resource allocation and reduce operational costs.
- Security & Compliance: Enforce enterprise-grade security protocols, ensuring data privacy and compliance with relevant industry regulations (GDPR, CCPA).
- Performance Tuning: Monitor system health and performance metrics, proactively identifying bottlenecks and implementing technical solutions to enhance throughput and latency.
- Team Leadership: Mentor junior engineers and collaborate with data science teams to translate complex AI requirements into technical infrastructure specifications.
Qualifications
- Education: Bachelor’s degree in Computer Science, Electrical Engineering, or a related field; Master’s degree is preferred.
- Experience: 5+ years of experience in software engineering, with at least 3 years specifically in infrastructure architecture or DevOps.
- Technical Skills: Deep expertise in cloud platforms (AWS, GCP, or Azure), containerization (Docker, Kubernetes), and orchestration.
- Programming: Proficiency in Python, Go, or Rust; experience with scripting languages for automation is required.
- AI Knowledge: Strong understanding of machine learning workflows, MLOps principles, and GPU infrastructure management.
- Soft Skills: Excellent problem-solving abilities, strong communication skills, and a proactive approach to technical challenges.