Job Description
Are you ready to build the infrastructure of tomorrow? OmniVerse Systems is seeking a visionary Lead AI Systems Architect to spearhead our operations in the 2026 era. We are not just adapting to the future; we are defining it.
In this pivotal role, you will bridge the gap between theoretical AI breakthroughs and scalable, production-grade software. You will architect systems capable of handling next-generation neural networks and quantum-enhanced computations.
Why You Belong Here:
We are a collective of futurists, engineers, and dreamers. We offer competitive equity packages, a remote-first culture, and the freedom to innovate without boundaries.
Responsibilities
- Architect Future-Proof AI Infra: Design and implement scalable distributed systems for high-frequency AI inference and learning loops.
- Lead R&D Strategy: Define the technical roadmap for integrating emerging technologies, including neuromorphic computing and edge AI.
- Model Governance: Establish frameworks for ethical AI, data privacy, and model explainability in a decentralized environment.
- Cross-Functional Leadership: Collaborate with product managers, data scientists, and security experts to deliver integrated solutions.
- Technical Mentorship: Foster a culture of excellence by mentoring junior architects and engineering teams.
- Performance Optimization: Continuously push the boundaries of latency and throughput for real-time AI applications.
Qualifications
- Education: Master’s degree in Computer Science, Artificial Intelligence, or a related field (PhD preferred).
- Experience: 10+ years in software engineering/architecture, with at least 5 years specializing in AI/ML systems.
- Technical Stack: Deep proficiency in Python, C++, and distributed computing frameworks (Kubernetes, Apache Spark).
- Domain Knowledge: Demonstrated experience with Large Language Models (LLMs), Transformer architectures, or Quantum computing interfaces.
- Soft Skills: Exceptional communication skills with the ability to translate complex technical concepts for non-technical stakeholders.
- Problem Solving: Proven track record of solving complex, ambiguous engineering challenges in fast-paced environments.