Job Description
Are you ready to define the technological landscape of 2026 and beyond? Nexus Horizon is seeking a visionary Senior AI Architect to lead the charge in building scalable, intelligent systems. We are not just building for today; we are engineering the infrastructure that will power the future.
In this pivotal role, you will bridge the gap between theoretical AI models and production-grade infrastructure. You will work closely with cross-functional teams to design robust systems that anticipate the scalability and security demands of the coming years. If you are passionate about the future of Artificial Intelligence and possess a deep understanding of system architecture, we want to meet you.
Why Join Nexus Horizon?
- Work on cutting-edge projects that define industry standards.
- Competitive compensation package and equity opportunities.
- Flexible remote-first culture with a vibrant SF office hub.
- Access to the latest hardware and cloud technologies.
Responsibilities
- Design and implement scalable AI and machine learning architectures capable of supporting high-volume enterprise demands.
- Lead the technical strategy for integrating GenAI models into our core product suite, ensuring alignment with 2026 roadmap goals.
- Mentor and guide junior engineers and data scientists, fostering a culture of innovation and technical excellence.
- Conduct rigorous code reviews and architecture assessments to ensure system integrity and performance.
- Collaborate with product managers to translate complex business requirements into technical blueprints.
- Optimize existing data pipelines for latency and cost-efficiency using modern cloud-native tools.
- Stay ahead of the curve on emerging AI trends, researching and evaluating new frameworks and libraries.
Qualifications
- 8+ years of experience in software engineering, with at least 3 years in a specialized AI/ML architecture role.
- Deep expertise in Python, TensorFlow, PyTorch, and cloud platforms (AWS, GCP, or Azure).
- Strong proficiency in system design patterns, microservices, and distributed systems.
- Proven track record of deploying large-scale machine learning models into production environments.
- Experience with MLOps tools (Kubernetes, Docker, MLflow) and CI/CD pipelines.
- Excellent communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.
- Master's degree in Computer Science, AI, or a related technical field is preferred.