Job Description
We are seeking a visionary Principal AI Architect to spearhead the 2026 Horizon Initiative, a groundbreaking research and development program focused on building the infrastructure for the next generation of autonomous generative intelligence. As a leader in this niche, you will define the architectural blueprint for systems that will power the enterprise of tomorrow, ensuring scalability, safety, and unprecedented performance.
Why Join Us?
We are not just building software; we are architecting the future. You will work with cutting-edge LLMs, reinforcement learning agents, and ethical AI frameworks to solve problems that don't even exist yet. If you are passionate about the trajectory of AI and want to be at the forefront of innovation, this is your opportunity to lead.
Responsibilities
- Architectural Vision: Design and implement scalable, fault-tolerant AI infrastructure capable of handling exascale data processing and complex model training.
- R&D Leadership: Lead a team of top-tier data scientists and engineers in pushing the boundaries of neural network capabilities for the 2026 roadmap.
- System Integration: Integrate disparate AI models and data streams into cohesive, real-time decision-making systems.
- Performance Optimization: Engineer solutions that reduce latency and improve inference accuracy for real-time applications.
- Ethical AI Governance: Establish and enforce guidelines for responsible AI usage, ensuring transparency and fairness in automated systems.
- Cross-Functional Collaboration: Partner with product and engineering teams to translate technical roadmaps into actionable development milestones.
- Mentorship: Cultivate a high-performance culture, mentoring junior architects and engineers on advanced AI methodologies.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Machine Learning, Mathematics, or a related quantitative field.
- Experience: 10+ years of experience in software engineering and at least 5 years in designing large-scale AI systems or deep learning architectures.
- Technical Skills: Expert proficiency in Python, PyTorch, TensorFlow, and distributed computing frameworks (Kubernetes, Apache Spark).
- Domain Knowledge: Deep understanding of Natural Language Processing (NLP), Large Language Models (LLMs), and Generative AI models.
- Problem Solving: Proven track record of solving complex, ambiguous technical problems in high-pressure environments.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders and executive leadership.
- Leadership: Demonstrated experience leading technical teams and managing cross-functional projects from conception to deployment.