Job Description
We are seeking a visionary Senior AI Architect (2026 Vision) to lead our engineering division into the next era of technological evolution. In an industry defined by rapid innovation, you will define the architectural blueprints for the next generation of intelligent systems. You will bridge the gap between theoretical breakthroughs and scalable production infrastructure, ensuring our solutions remain at the forefront of the 2026 technology landscape.
At QuantumHorizon Labs, we don't just predict the future; we build it. We are looking for a leader who thrives in ambiguity and possesses the foresight to design systems that remain relevant, powerful, and secure through 2026 and beyond.
Why Join Us?
- Work on cutting-edge AI infrastructure that defines the future of enterprise.
- Competitive compensation package and equity opportunities.
- Flexible remote-first culture with access to world-class amenities in SF.
- Continuous learning and development budget.
Responsibilities
- Architectural Leadership: Design and implement scalable, high-performance AI infrastructure aligned with 2026 technological standards and future-proofing principles.
- AI Strategy: Lead the architectural strategy for Large Language Models (LLMs), generative AI integration, and autonomous agent systems.
- Collaboration: Collaborate with cross-functional teams to translate high-level business requirements into detailed technical roadmaps and prototypes.
- Security & Ethics: Ensure data integrity, robust security protocols, and ethical AI deployment across all platforms and user touchpoints.
- Innovation: Drive technical innovation through research, proof-of-concept (PoC) development, and the adoption of emerging technologies.
- Mentorship: Mentor junior engineers and senior staff alike, establishing best practices for code quality, system resilience, and AI governance.
Qualifications
- Experience: Minimum of 8 years of experience in software architecture, with at least 3 years specifically in AI/ML engineering and system design.
- Technical Stack: Proven expertise in Python, TensorFlow, PyTorch, and cloud-native architectures (AWS, GCP, or Azure).
- Deep Learning: Deep understanding of neural network architectures, optimization techniques, MLOps, and distributed computing.
- Problem Solving: Strong problem-solving skills with a focus on solving complex, multi-dimensional problems in high-stakes environments.
- Communication: Excellent communication skills with the ability to articulate complex technical concepts to non-technical stakeholders.
- Adaptability: Ability to navigate ambiguity and pivot strategies in a fast-paced, evolving technological landscape.