Job Description
Are you ready to architect the future? Nexus Future Labs is seeking a visionary Lead AI Architect to spearhead our 2026 Horizon Initiative. We are building the infrastructure for the next generation of intelligent systems, and we need a technical leader who can bridge the gap between cutting-edge research and scalable production deployment.
In this pivotal role, you will define the architectural roadmap for our AI platforms, ensuring they are robust, secure, and future-proof. You will collaborate with cross-functional teams of data scientists, engineers, and product managers to deliver transformative solutions that push the boundaries of what is possible.
Why Join Us?
• Work on mission-critical projects that define the industry standard for 2026.
• Competitive compensation package with equity options.
• Flexible remote-first culture with state-of-the-art equipment.
Responsibilities
- Architectural Vision: Design and implement scalable system architectures for large-scale AI models and neural networks, focusing on high availability and low latency.
- Strategic Leadership: Define the technical roadmap for the 2026 Horizon Initiative, aligning engineering capabilities with long-term business goals.
- Team Mentorship: Lead, mentor, and grow a high-performing team of AI engineers and data scientists, fostering a culture of innovation and excellence.
- Model Deployment: Oversee the end-to-end deployment of machine learning models into production environments using containerization (Docker/Kubernetes) and CI/CD pipelines.
- Technical Governance: Establish best practices for code quality, security, and ethical AI usage across the organization.
- Stakeholder Communication: Translate complex technical concepts into actionable insights for executive stakeholders and non-technical team members.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- Experience: 8+ years of experience in software engineering and 5+ years in designing and deploying machine learning systems at scale.
- Technical Expertise: Deep proficiency in Python, TensorFlow, PyTorch, and distributed computing frameworks (Spark, Ray).
- Infrastructure: Strong experience with cloud platforms (AWS, GCP, or Azure) and infrastructure-as-code tools (Terraform, CloudFormation).
- Problem Solving: Proven track record of solving complex technical challenges in NLP, Computer Vision, or Reinforcement Learning.
- Leadership: Demonstrated ability to lead cross-functional teams and manage technical projects from conception to delivery.