Job Description
Join the Architects of Tomorrow
Nexus Future Labs is on a mission to define the technological landscape of 2026 and beyond. We are seeking a visionary Principal AI Architect to lead our R&D division, focusing on next-generation generative models and autonomous system integration.
In this pivotal role, you will bridge the gap between theoretical AI research and production-ready infrastructure. You will be responsible for architecting systems that are not only scalable today but are future-proofed for the rapid advancements expected by 2026. If you thrive in high-stakes environments and possess an obsession with performance and ethics in AI, we want to hear from you.
Why Join Us?
- Work with state-of-the-art hardware (TPU clusters, quantum simulators).
- Competitive equity package with long-term vesting.
- Flexible remote-first culture with quarterly innovation sprints.
Responsibilities
- Architect the 2026 Roadmap: Define the technical vision for our long-term AI capabilities, ensuring our infrastructure can handle the computational demands of future algorithms.
- Model Development: Lead the design and implementation of advanced Large Language Models (LLMs) and multimodal AI systems focused on safety and efficiency.
- System Optimization: Oversee the deployment of models on edge devices and cloud infrastructure, optimizing for latency and throughput.
- Talent Leadership: Mentor a team of senior engineers and data scientists, fostering a culture of innovation and continuous learning.
- Strategic Partnerships: Collaborate with product and engineering teams to integrate AI solutions that solve real-world problems.
- Compliance & Ethics: Ensure all AI systems adhere to strict ethical guidelines and data privacy regulations.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Artificial Intelligence, or a related field.
- Experience: 8+ years of experience in software engineering, with at least 4 years specifically focused on AI/ML architecture.
- Technical Stack: Proficiency in Python, C++, and frameworks such as PyTorch, TensorFlow, or JAX.
- AI Expertise: Deep understanding of neural networks, transformer architectures, and reinforcement learning.
- Cloud Mastery: Proven track record of designing scalable systems on AWS, GCP, or Azure.
- Problem Solving: Ability to troubleshoot complex architectural issues and think critically about system scalability.