Job Description
We are not just building software; we are architecting the infrastructure of the future. Nexus Horizon Labs is at the forefront of the 2026 AI Evolution, pioneering autonomous agents and next-generation multimodal learning systems. We are seeking a visionary Lead AI Architect to lead the technical vision for our flagship product roadmap.
In this role, you will bridge the gap between theoretical AI research and production-grade engineering. You will define the architectural patterns that enable our systems to scale from prototype to a global platform serving millions. If you are passionate about the trajectory of Artificial General Intelligence (AGI) and want to be a key builder of the 2026 landscape, we want to hear from you.
Responsibilities
- Architect the 2026 Roadmap: Define the high-level technical architecture for our autonomous AI agents and multimodal learning models.
- System Scalability: Design distributed, fault-tolerant systems capable of handling high-throughput data streams and real-time inference.
- Research Integration: Translate cutting-edge academic research papers into production-ready code and scalable infrastructure.
- Model Optimization: Lead initiatives to optimize Large Language Models (LLMs) for edge deployment and reduced latency.
- Technical Leadership: Mentor a team of senior engineers and data scientists, fostering a culture of innovation and rigorous engineering standards.
- Collaboration: Work closely with product managers and stakeholders to align technical roadmaps with business objectives.
- Security & Compliance: Implement robust security protocols to ensure data privacy and model integrity in a decentralized environment.
Qualifications
- Education: Master’s or PhD degree in Computer Science, Mathematics, Physics, or a related field (or equivalent practical experience).
- Experience: 7+ years of experience in software engineering, with at least 3 years in a lead or architect role specifically within AI/ML.
- Technical Stack: Proficiency in Python, C++, and experience with deep learning frameworks (PyTorch, TensorFlow, JAX).
- Architecture: Deep understanding of distributed systems, microservices, cloud-native architectures (AWS, GCP, Azure), and Kubernetes.
- AI Expertise: Strong background in Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning.
- Problem Solving: Proven track record of solving complex, ambiguous problems in fast-paced environments.