Job Description
We are on a mission to define the technological landscape of 2026 and beyond. Quantum Leap Technologies is seeking a visionary Senior AI Architect to lead our research into next-generation autonomous systems and advanced machine learning models. In this pivotal role, you will design the infrastructure that will power the next era of intelligent applications, ensuring scalability, security, and ethical AI practices.
You will be working in a high-performance environment where innovation is not just encouraged but required. If you are passionate about pushing the boundaries of what is possible with Artificial Intelligence and want to shape the future of the industry, we want to hear from you.
You will be working in a high-performance environment where innovation is not just encouraged but required. If you are passionate about pushing the boundaries of what is possible with Artificial Intelligence and want to shape the future of the industry, we want to hear from you.
Responsibilities
- Design and Deployment: Architect scalable, high-performance AI infrastructure capable of handling petabyte-scale data and real-time processing.
- R&D Leadership: Lead research and development initiatives focusing on Agentic AI, Large Language Models (LLMs), and predictive analytics for 2026.
- Technical Strategy: Define and execute the long-term technical roadmap for AI adoption across the organization.
- Team Mentorship: Mentor a team of world-class machine learning engineers and data scientists, fostering a culture of continuous learning and excellence.
- Collaboration: Partner with product managers, engineers, and stakeholders to translate complex AI capabilities into user-centric products.
- Compliance: Ensure all AI systems adhere to ethical guidelines, data privacy regulations, and industry best practices.
Qualifications
- Education: Master’s or PhD in Computer Science, Machine Learning, or a related technical field.
- Experience: 8+ years of experience in software engineering with at least 5 years specifically in AI/ML architecture.
- Technical Skills: Deep proficiency in Python, TensorFlow, PyTorch, and modern cloud platforms (AWS, GCP, or Azure).
- Expertise: Proven experience designing and deploying LLMs, fine-tuning models, and implementing Retrieval-Augmented Generation (RAG) pipelines.
- Soft Skills: Exceptional leadership skills with the ability to communicate complex technical concepts to non-technical stakeholders.
- Problem Solving: Demonstrated ability to solve complex, ambiguous problems in a fast-paced startup environment.