Job Description
Are you ready to architect the future? Nexus Horizon Labs is seeking a visionary Senior AI Architect to lead our 2026 strategic initiatives. We are not just building software; we are designing the intelligent infrastructure for the next era of human-machine collaboration. In this role, you will define the architectural framework for autonomous agents, generative AI ecosystems, and quantum-ready neural networks.
As a key player in our 2026 roadmap, you will bridge the gap between theoretical machine learning breakthroughs and scalable, production-grade engineering. You will mentor a team of elite engineers and set the technical standards for the next decade of innovation.
Responsibilities
- Architect 2026-Ready Systems: Design and implement high-availability, distributed AI infrastructure capable of handling petabyte-scale data streams with sub-millisecond latency.
- Lead Generative AI Strategy: Spearhead the development of proprietary Large Language Models (LLMs) and multimodal agents, optimizing for safety, hallucination reduction, and real-time adaptability.
- Quantum-Cloud Integration: Collaborate with quantum computing research teams to integrate hybrid quantum-classical algorithms into our core product suite.
- Engineering Excellence: Establish and enforce rigorous code quality standards, CI/CD pipelines, and MLOps best practices to ensure deployment reliability.
- Talent Development: Mentor junior and senior engineers, fostering a culture of continuous learning and technical excellence within the AI research division.
- Ethical AI Governance: Lead the charge in establishing ethical AI guidelines, ensuring fairness, transparency, and accountability in all automated decision-making systems.
Qualifications
- Master’s Degree or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- 10+ years of experience in software engineering, with at least 5 years specifically focused on Deep Learning, NLP, or Reinforcement Learning.
- Expert proficiency in Python, C++, and Rust, with deep experience in frameworks such as PyTorch, TensorFlow, or JAX.
- Proven track record of deploying large-scale AI models in production environments (e.g., AWS, GCP, Azure) with high availability.
- Experience with Quantum Computing libraries (Qiskit, Cirq) or hybrid classical-quantum algorithms is highly preferred.
- Strong leadership skills with a history of successfully managing cross-functional teams and driving technical roadmaps.
- Familiarity with AI safety and alignment principles, including red-teaming methodologies.