Job Description
We are seeking a visionary Lead AI Architect to spearhead our engineering team in defining the technological landscape for the year 2026. In an era defined by rapid AI evolution, you will be at the forefront of integrating next-generation neural architectures and predictive analytics into our core products. This is not just a job; it is a mandate to future-proof our infrastructure and set the standard for enterprise-grade artificial intelligence.
As a pivotal member of our CTO office, you will bridge the gap between theoretical AI research and scalable, production-ready code. You will mentor a team of elite engineers and collaborate with product leaders to translate complex data strategies into tangible business outcomes.
Why Join Us?
- Work on projects that define the AI landscape for 2026 and beyond.
- Competitive compensation and equity package.
- Flexible hybrid work environment in the heart of Silicon Valley.
Responsibilities
- Architect and design scalable AI systems capable of handling petabyte-scale data for the 2026 roadmap.
- Lead the research and implementation of cutting-edge Large Language Models (LLMs) and generative AI tools.
- Establish best practices for MLOps, ensuring model deployment, monitoring, and retraining pipelines are robust.
- Collaborate with cross-functional teams to identify high-impact AI use cases that drive revenue and efficiency.
- Define the technical vision and architectural guidelines for the engineering department.
- Drive innovation in edge computing and real-time AI processing.
Qualifications
- 10+ years of experience in software engineering, with at least 5 years in a senior or lead architecture role.
- Deep expertise in machine learning frameworks (TensorFlow, PyTorch) and programming languages (Python, C++).
- Proven track record of deploying large-scale AI systems in production environments.
- Strong background in cloud infrastructure (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Excellent leadership skills with a history of mentoring high-performing engineering teams.
- Familiarity with ethical AI practices and regulatory compliance in data privacy.