Job Description
Are you ready to architect the future of Artificial Intelligence? Nexus Horizon is seeking a visionary Lead AI Architect to define the technical roadmap for 2026 and beyond.
We are not just building AI models; we are building the infrastructure that will power the next generation of human-machine interaction. In this pivotal role, you will bridge the gap between theoretical research and scalable production systems, ensuring our platforms are robust, efficient, and ethically sound.
Why Nexus Horizon?
- Impact: Work on projects that define the industry standard for Generative AI.
- Growth: Competitive equity and professional development in a cutting-edge environment.
- Flexibility: Hybrid work model with a focus on output over hours.
If you thrive in ambiguity and love solving complex system design challenges, we want to meet you.
Responsibilities
- Architectural Leadership: Design and oversee the development of high-scale distributed AI infrastructure capable of handling millions of concurrent requests.
- Model Deployment: Lead the transition from prototype to production for Large Language Models (LLMs) and neural networks.
- System Optimization: Continuously monitor system performance, reducing latency and optimizing resource utilization.
- Collaboration: Partner with Data Scientists and Product Managers to align technical roadmaps with business goals.
- Best Practices: Establish coding standards, CI/CD pipelines, and monitoring protocols for the AI engineering team.
- Future-Proofing: Research emerging technologies and frameworks to ensure our stack remains relevant through 2026 and beyond.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Machine Learning, or a related technical field.
- Experience: 7+ years of software engineering experience, with at least 3 years specifically in AI/ML infrastructure.
- Technical Stack: Deep expertise in Python, PyTorch, TensorFlow, and distributed computing frameworks like Kubernetes and Docker.
- Cloud Mastery: Proven track record designing scalable solutions on AWS, GCP, or Azure.
- LLM Expertise: Hands-on experience deploying and fine-tuning models like GPT-4, LLaMA, or similar architectures.
- Soft Skills: Exceptional communication skills with the ability to translate complex technical concepts for non-technical stakeholders.