Job Description
About 2026
We are building the infrastructure for the future. At 2026, we aren't just predicting trends; we are architecting the reality of the year 2026 and beyond. We are seeking a visionary Lead AI Architect to lead our core intelligence division, ensuring our systems are scalable, secure, and at the forefront of artificial general intelligence.
The Role
You will be the technical steward of our AI strategy, bridging the gap between theoretical machine learning breakthroughs and production-grade software engineering. You will lead a world-class team of engineers, data scientists, and researchers to build the next generation of autonomous systems.
Responsibilities
- System Architecture: Design and oversee the end-to-end architecture of large-scale AI models, ensuring high availability, scalability, and fault tolerance.
- Team Leadership: Mentor senior engineers and junior developers, fostering a culture of innovation and technical excellence.
- R&D Strategy: Evaluate emerging technologies (e.g., LLMs, Reinforcement Learning) and integrate them into our product roadmap.
- Performance Optimization: Drive initiatives to reduce inference latency and optimize model training cycles.
- Security & Ethics: Implement robust security protocols and ensure AI systems adhere to ethical guidelines and compliance standards.
- Cross-Functional Collaboration: Partner with product managers, designers, and stakeholders to define technical requirements and deliver impactful solutions.
Qualifications
- Education: Master’s or PhD degree in Computer Science, Mathematics, or a related technical field (or equivalent practical experience).
- Experience: 8+ years of experience in software engineering, with at least 4 years in a leadership role designing AI/ML systems.
- Technical Skills: Deep expertise in Python, TensorFlow, PyTorch, or similar frameworks. Experience with distributed computing systems (Kubernetes, AWS, GCP) is required.
- Problem Solving: Proven track record of solving complex, large-scale technical challenges in high-pressure environments.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders and executive leadership.
- Certifications: AWS Solutions Architect or Google Cloud Professional Machine Learning Engineer preferred.