Job Description
We are Nexus Horizon Systems, a pioneer in next-generation computing. We are not just building for today; we are engineering the infrastructure that will define the year 2026. We are seeking a visionary Lead AI Architect to spearhead our '2026 Horizon Initiative,' a groundbreaking project focused on adaptive autonomous systems and next-gen neural architectures.
In this role, you will bridge the gap between theoretical research and scalable production systems. You will lead a team of elite engineers and data scientists to build AI agents that can reason, adapt, and operate independently in complex, real-world environments.
Why Join Us?
• Work on the bleeding edge of technology with a multi-billion dollar R&D budget.
• Flexible remote-first culture with headquarters in the heart of Silicon Valley.
• Competitive equity package and top-tier health benefits.
• Direct access to executive leadership and autonomy in technical decision-making.
Responsibilities
- Define the 2026 Roadmap: Architect the technical vision and execution plan for AI capabilities expected in the 2026 timeframe, including agentic workflows and edge-computing integration.
- System Design: Design and implement scalable, fault-tolerant AI infrastructure capable of processing petabytes of data with sub-millisecond latency.
- Research & Development: Lead internal R&D initiatives exploring emerging paradigms such as Neuromorphic Computing, Quantum-AI hybrid models, and Federated Learning.
- Team Leadership: Mentor a high-performing team of ML engineers and researchers, fostering a culture of innovation and technical excellence.
- Product Integration: Collaborate closely with product managers and engineering teams to integrate cutting-edge AI models into our core software ecosystem.
- Security & Ethics: Ensure all AI systems adhere to strict ethical guidelines, bias mitigation protocols, and data privacy regulations (GDPR/CCPA).
Qualifications
- Education: PhD or Master’s degree in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 8+ years of experience in software engineering, with at least 5 years specifically focused on Machine Learning and Deep Learning.
- Technical Skills: Deep proficiency in Python, PyTorch, TensorFlow, and C++. Experience with distributed computing frameworks (Kubernetes, Apache Spark) is mandatory.
- Domain Knowledge: Strong understanding of Large Language Models (LLMs), Transformer architectures, and Reinforcement Learning from Human Feedback (RLHF).
- Soft Skills: Exceptional communication skills with the ability to translate complex technical concepts to non-technical stakeholders. Demonstrated leadership in cross-functional teams.