Job Description
We are looking for a visionary 2026 AI Architect to lead the next generation of generative intelligence systems. Nexus Horizon is building the infrastructure for tomorrow's reality, and we need a technical leader who can bridge the gap between theoretical research and scalable production deployment.
In this role, you will define the architectural roadmap for our flagship product, ensuring our AI models remain at the cutting edge of performance and ethical safety by the year 2026. You will work closely with our engineering, product, and research teams to design systems that are not only powerful but also explainable and fair.
If you are passionate about the future of artificial intelligence and want to leave a lasting legacy in the tech industry, we want to meet you.
Responsibilities
- Architect Scalable Solutions: Design and implement robust AI infrastructure that can handle millions of concurrent requests with sub-millisecond latency.
- Lead the 2026 Roadmap: Collaborate with stakeholders to define technical milestones and delivery schedules for upcoming product releases.
- Model Optimization: Conduct rigorous optimization of neural networks, focusing on inference speed, memory efficiency, and energy consumption.
- Cross-Functional Leadership: Mentor junior engineers and data scientists, conducting code reviews and architectural deep-dives to ensure best practices are followed.
- Risk Management: Identify potential security vulnerabilities and ethical bias in AI models, implementing mitigation strategies before production deployment.
Qualifications
- Education: Bachelor’s degree in Computer Science, Mathematics, or a related field (Master’s or PhD preferred).
- Experience: 8+ years of experience in software engineering, with at least 5 years specifically focused on Artificial Intelligence and Machine Learning.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and distributed computing frameworks (e.g., Kubernetes, Apache Spark).
- System Design: Deep understanding of microservices architecture, cloud platforms (AWS/GCP), and large-scale data pipelines.
- Innovation: Proven track record of publishing research or shipping innovative AI products to market.