Job Description
Are you ready to engineer the future of intelligence? Quantum Horizon Systems is a forward-thinking pioneer in artificial intelligence infrastructure, and we are seeking a visionary Lead AI Architect (2026 Vision) to define the technical backbone of our next-generation platforms.
In this pivotal role, you will bridge the gap between theoretical AI breakthroughs and scalable, robust software engineering. You will be responsible for architecting systems that are not just efficient today, but resilient and adaptive for the year 2026 and beyond. Join us in shaping the digital landscape and solving complex challenges at the intersection of machine learning and high-performance computing.
Why join us?
- Work on cutting-edge AI infrastructure projects.
- Competitive compensation and equity package.
- Flexible remote-first culture with a vibrant San Francisco hub.
- Opportunity to mentor the next generation of engineering talent.
Responsibilities
- Design and oversee the end-to-end architecture of scalable AI and machine learning systems, ensuring they meet 2026 performance standards.
- Lead a diverse team of engineers and data scientists, fostering a culture of innovation and technical excellence.
- Define technical strategy, roadmap, and best practices for code quality, security, and deployment.
- Collaborate with product managers and stakeholders to translate business requirements into technical solutions.
- Drive the adoption of next-generation cloud technologies, edge computing, and microservices.
- Conduct deep-dive code reviews and architecture reviews to mitigate technical debt and risks.
Qualifications
- 10+ years of experience in software architecture, with at least 5 years in a Lead or Architect role.
- Expert proficiency in programming languages such as Python, Java, or Go.
- Deep understanding of distributed systems, cloud architecture (AWS/Azure/GCP), and containerization (Kubernetes/Docker).
- Proven track record of deploying and managing large-scale machine learning infrastructure.
- Strong experience with data engineering pipelines and big data technologies (Spark, Hadoop).
- Master’s degree in Computer Science, Engineering, or a related field is highly preferred.