Job Description
We are at the precipice of a technological revolution, and OmniFuture Systems is building the infrastructure for the year 2026. We are seeking a visionary Principal AI Architect to lead our flagship initiative: the 2026 Protocol. This is not just a job; it is a mission to architect the neural backbone of the next digital era.
In this high-impact role, you will define the architectural strategies for our next-generation Large Language Models (LLMs) and autonomous agents. You will work directly with C-level leadership to ensure our systems are scalable, secure, and future-proofed for the rapid advancements expected by 2026.
If you are a technical leader passionate about the intersection of quantum computing, generative AI, and enterprise scalability, we want to meet you.
Responsibilities
- Lead the 2026 Protocol: Define and execute the architectural vision for the next generation of AI infrastructure, ensuring alignment with the 2026 strategic roadmap.
- System Design: Design complex, distributed AI systems capable of handling petabyte-scale data with real-time latency requirements.
- Technology Selection: Evaluate and integrate emerging technologies (e.g., WebGPU, Neuromorphic computing) to stay ahead of the 2026 technology curve.
- Mentorship: Foster a culture of innovation by mentoring senior engineers and guiding the technical roadmap for the AI research division.
- Cross-Functional Collaboration: Partner with product, security, and operations teams to ensure seamless deployment of AI solutions across global markets.
- Performance Optimization: Continuously refine model inference pipelines to maximize efficiency and reduce operational costs.
- R&D Strategy: Identify gaps in the current stack and drive proof-of-concept (PoC) initiatives for future-proof solutions.
Qualifications
- Education: Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related technical field (PhD preferred).
- Experience: 10+ years of experience in software architecture, with at least 5 years dedicated to AI/ML systems design.
- Technical Proficiency: Deep expertise in Python, C++, and frameworks such as PyTorch, TensorFlow, or JAX.
- Architecture: Proven track record of designing scalable cloud-native architectures on AWS, Azure, or Google Cloud Platform (GCP).
- AI Knowledge: Strong understanding of LLMs, Transformers, RAG (Retrieval-Augmented Generation), and fine-tuning methodologies.
- Leadership: Demonstrated ability to lead high-performance teams and manage cross-functional projects from conception to delivery.
- Communication: Exceptional ability to translate complex technical concepts into strategic business value for stakeholders.