Job Description
We are on the brink of a technological revolution, and we need a visionary leader to architect our future for the year 2026. At Nexus Horizon Technologies, we are not just building software; we are defining the trajectory of human-machine interaction. We are seeking a Lead AI Architect (2026 Vision) to join our elite engineering team in San Francisco.
In this pivotal role, you will spearhead the design and implementation of our next-generation AI infrastructure, ensuring our systems are scalable, secure, and capable of handling the complexities of the future. You will work at the intersection of research and production, bridging the gap between theoretical AI breakthroughs and real-world applications.
If you are a technical expert who thrives in ambiguity and is passionate about shaping the technological landscape of the next decade, we want to hear from you.
Responsibilities
- Architect and lead the development of scalable AI frameworks and infrastructure designed for the 2026 technological landscape.
- Define the technical vision and roadmap for AI research and deployment, ensuring alignment with company strategic goals.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to integrate AI solutions into core products.
- Oversee the selection and optimization of machine learning tools, libraries, and hardware accelerators.
- Mentor junior engineers and architects, fostering a culture of technical excellence and innovation.
- Conduct rigorous code reviews and ensure system reliability, security, and performance at scale.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field; Ph.D. preferred.
- 7+ years of experience in software engineering, with at least 3 years in a lead or architect role focusing on AI/ML systems.
- Deep expertise in Python, PyTorch, TensorFlow, or similar machine learning frameworks.
- Strong understanding of distributed systems, cloud architecture (AWS, GCP, or Azure), and containerization technologies (Docker, Kubernetes).
- Proven track record of deploying production-grade AI models and managing large-scale data pipelines.
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.