Job Description
We are on the precipice of a technological singularity, and we are looking for a visionary Future of AI Architect to help us design the infrastructure for the year 2026 and beyond. As the pace of generative AI accelerates, we need a technical leader who can bridge the gap between theoretical quantum computing breakthroughs and practical, scalable software solutions.
In this role, you will not just be coding; you will be architecting the future. You will lead a team of elite engineers in developing next-generation neural networks that are optimized for post-silicon computing architectures. If you are passionate about the intersection of AGI (Artificial General Intelligence), spatial computing, and human-machine interfaces, this is your opportunity to define the standard for the decade.
Why Join Us?
- Work on cutting-edge projects that will shape the reality of 2026.
- Competitive salary and equity package.
- Unlimited PTO and flexible remote/hybrid work policies.
- Access to state-of-the-art quantum simulation labs.
Responsibilities
- Architect Next-Gen Systems: Design and oversee the implementation of large-scale distributed systems capable of handling exascale computing loads for advanced AI models.
- Quantum Integration: Develop hybrid algorithms that effectively leverage existing quantum processors alongside classical hardware to solve complex computational problems.
- Strategic Roadmapping: Define the technical roadmap for the company's AI evolution, ensuring readiness for regulatory and technological shifts anticipated by 2026.
- Team Leadership: Mentor senior engineers and data scientists, fostering a culture of innovation and rigorous technical excellence.
- Performance Optimization: Lead initiatives to reduce latency in real-time inference engines, essential for AR/VR applications.
- R&D Collaboration: Partner with academic institutions to stay ahead of emerging trends in neuromorphic computing and synthetic data generation.
Qualifications
- Experience: 10+ years of experience in software architecture, with at least 5 years specifically focused on Machine Learning infrastructure and high-performance computing (HPC).
- Education: Master’s or PhD in Computer Science, Mathematics, or a related field is strongly preferred.
- Technical Skills: Deep expertise in Python, C++, and Rust; familiarity with TensorFlow, PyTorch, and quantum computing libraries (Qiskit, Cirq).
- Future-Forward Mindset: Demonstrated ability to anticipate industry trends and adapt technical strategies to emerging paradigms.
- Leadership: Proven track record of leading high-performance engineering teams through complex product lifecycles.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders and investors.