Job Description
Are you ready to shape the technological landscape of 2026?
Nexus Future Systems is pioneering the next generation of cognitive computing, and we are seeking a visionary Lead AI Architect (2026 Vision) to join our elite team in San Francisco. As we prepare to launch our flagship quantum-assisted neural network, we need an engineer who doesn't just write code, but architects the future.
In this pivotal role, you will lead the technical strategy for our 2026 roadmap, ensuring our AI infrastructure is scalable, secure, and ready for the exponential growth of artificial general intelligence. You will bridge the gap between theoretical research and practical application, working with world-class researchers to deploy models that redefine human-machine interaction.
Why join us?
- Work on projects that define the standards for 2026 and beyond.
- Competitive compensation package including equity.
- Access to cutting-edge hardware and proprietary datasets.
- Flexible remote-first culture with a central hub in San Francisco.
Responsibilities
- Architect Next-Gen AI Frameworks: Design and oversee the implementation of scalable AI architectures specifically tailored for the 2026 technological horizon, including generative models and predictive analytics.
- Lead Technical Strategy: Define the long-term technical roadmap for the AI division, aligning engineering goals with business objectives and future market trends.
- Optimize Neural Networks: Drive research and development initiatives to reduce latency and improve the accuracy of our core AI models by 40% year-over-year.
- Collaborate with Research Teams: Partner with PhD researchers to translate complex algorithms into production-ready code and deployable microservices.
- Code Quality & Mentorship: Establish rigorous engineering standards, conduct high-level code reviews, and mentor junior and senior engineers to foster a culture of excellence.
- Security & Compliance: Implement robust security protocols to protect sensitive data and ensure full compliance with emerging global AI regulations in 2026.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related field; PhD preferred.
- Experience: Minimum 8+ years of professional experience in software engineering, with at least 4 years specifically focused on Machine Learning and Deep Learning architecture.
- Technical Proficiency: Deep expertise in Python, C++, and frameworks such as PyTorch, TensorFlow, or JAX.
- Leadership: Proven track record of leading engineering teams, managing cross-functional projects, and delivering complex systems on tight deadlines.
- Future-Forward Thinking: Demonstrated ability to anticipate industry shifts and adapt systems architecture to meet the demands of emerging technologies (e.g., Quantum AI, Edge Computing).
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders and executive leadership.