Job Description
Are you ready to build the intelligence of tomorrow? Nexus Horizon is seeking a visionary Senior AI Architect to lead the development of next-gen systems for 2026 and beyond. We are not just building software; we are architecting the cognitive layer of the digital world.
In this high-impact role, you will define the technical strategy for our generative AI initiatives, ensuring our solutions are scalable, ethical, and groundbreaking. You will work at the intersection of deep learning, systems engineering, and product innovation.
Why Join Us?
- Future-Ready Tech Stack: Work with cutting-edge LLMs, vector databases, and edge computing architectures.
- Impact: Your work will directly influence how billions of users interact with AI in the coming decade.
- Equity & Culture: Competitive compensation package with meaningful equity and a culture that values radical candor and continuous learning.
Responsibilities
- Architect LLM Solutions: Design and implement scalable, secure, and efficient large language model architectures tailored for enterprise applications.
- Technical Leadership: Provide technical guidance to engineering teams, setting best practices for MLOps, model deployment, and data governance.
- Model Optimization: Oversee the fine-tuning and optimization of pre-trained models to ensure high performance and low latency.
- R&D Strategy: Stay ahead of industry trends to evaluate and integrate emerging AI technologies (e.g., multi-modal AI, autonomous agents) into our roadmap.
- Ethical AI Compliance: Ensure all AI systems adhere to strict ethical guidelines, safety protocols, and regulatory standards.
- Stakeholder Communication: Translate complex technical concepts into clear strategies for non-technical stakeholders and product managers.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field; PhD preferred.
- Experience: 5+ years of experience in software engineering or data science, with at least 2 years in a lead architect role focusing on AI/ML.
- Technical Skills: Deep expertise in Python, PyTorch, TensorFlow, and distributed computing frameworks.
- Modeling: Proven experience designing and deploying production-grade machine learning models.
- Problem Solving: Strong analytical skills with the ability to troubleshoot complex system failures and optimize performance bottlenecks.
- Soft Skills: Exceptional communication skills and a track record of leading cross-functional teams.