Job Description
Are you ready to define the technological landscape of the future? OmniFuture Innovations is seeking a visionary Lead AI & Quantum Integration Architect to spearhead our mission toward the 2026 technological horizon. As we bridge the gap between current machine learning paradigms and next-generation quantum computing, you will be at the epicenter of innovation.
In this pivotal role, you will not only design robust systems but also mentor a world-class team of engineers and researchers. We are looking for a thought leader who is passionate about solving unsolvable problems and building the infrastructure that will power the next decade of human advancement.
Why join us?
• Work on cutting-edge projects that will shape the future of computing.
• Competitive compensation package with equity options.
• Flexible remote-first culture with state-of-the-art facilities in San Francisco.
Responsibilities
- Architect and implement scalable hybrid systems that integrate classical AI models with quantum processing units (QPUs).
- Lead the research and development of novel algorithms optimized for quantum environments.
- Define technical vision and roadmaps for the engineering department, specifically focusing on 2026 readiness.
- Establish best practices for quantum data security, error correction, and ethical AI governance.
- Mentor and cultivate a high-performance engineering team through code reviews, technical discussions, and career development.
- Collaborate with cross-functional stakeholders to translate business requirements into technical architecture.
Qualifications
- Master’s or PhD in Computer Science, Physics, Applied Mathematics, or a related quantitative field.
- 10+ years of experience in software engineering, with at least 5 years in AI/ML architecture or Quantum Computing.
- Deep practical experience with quantum computing frameworks (e.g., Qiskit, Cirq, PyQuil, or Azure Quantum).
- Proficiency in Python, C++, and distributed systems design patterns.
- Proven track record of leading high-performing engineering teams in a fast-paced environment.
- Strong understanding of cloud infrastructure (AWS, Azure, or GCP) and containerization technologies (Docker, Kubernetes).