Job Description
We are on a mission to define the technological landscape of 2026 and beyond. Quantum Horizon Labs is seeking a visionary Future-Ready AI Architect to lead our next-generation generative intelligence initiatives. You won't just be maintaining systems; you will be architecting the infrastructure that powers the autonomous enterprises of tomorrow.
In this pivotal role, you will bridge the gap between theoretical AI capabilities and scalable, production-ready solutions. You will collaborate with world-class researchers and engineers to build intelligent systems that anticipate user needs and drive unprecedented growth.
Why Join Us?
- Work on cutting-edge Generative AI and Large Language Model (LLM) integration.
- Shape the strategic roadmap for AI adoption in a rapidly evolving market.
- Competitive compensation package with equity options.
What You Will Do:
As our Future-Ready AI Architect, you will take full ownership of our AI infrastructure, ensuring it is resilient, scalable, and secure.
Responsibilities
- Design and implement scalable, fault-tolerant AI architectures capable of handling high-volume data streams.
- Lead the research and integration of emerging AI technologies, specifically focusing on Generative AI and predictive analytics for the 2026 horizon.
- Collaborate with product and engineering teams to translate complex business requirements into robust technical AI solutions.
- Establish best practices for data governance, model deployment, and MLOps pipelines.
- Mentor junior engineers and data scientists, fostering a culture of innovation and continuous learning.
- Conduct rigorous testing and validation to ensure AI models meet safety and ethical standards.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related technical field.
- 10+ years of experience in software engineering, with at least 5 years specifically in AI/ML architecture.
- Deep expertise in Python, TensorFlow, PyTorch, and modern MLOps tools.
- Proven track record of deploying Large Language Models (LLMs) and Generative AI models in production environments.
- Strong understanding of cloud platforms (AWS, GCP, or Azure) and microservices architecture.
- Excellent leadership skills with the ability to communicate complex technical concepts to non-technical stakeholders.