Job Description
We are seeking a visionary Lead AI Architect to spearhead our groundbreaking "Year 2026" initiative. In an era defined by rapid technological evolution, your role will be pivotal in architecting scalable, intelligent systems that bridge the gap between today’s capabilities and tomorrow’s realities.
As a key member of our elite engineering team, you will define the technical roadmap for our upcoming generation of autonomous agents and generative platforms. If you are passionate about building the infrastructure of the future and thrive in a fast-paced, high-stakes environment, we want to hear from you.
Why Join Us?
- Work on cutting-edge AI infrastructure for the 2026 roadmap.
- Competitive compensation package with equity options.
- Flexible remote-first culture with premium Seattle amenities.
Responsibilities
- Lead the architectural design for next-generation AI infrastructure targeting the 2026 release cycle, ensuring scalability and security.
- Oversee the integration of advanced machine learning models into enterprise-grade cloud environments (AWS/Azure/GCP).
- Collaborate with cross-functional teams of data scientists and product managers to translate business requirements into technical blueprints.
- Mentor junior engineers and establish best practices for code quality, testing, and deployment.
- Conduct technical feasibility studies and evaluate emerging technologies to drive innovation.
- Define and implement robust monitoring and observability strategies for complex distributed systems.
- Drive the migration strategy for legacy systems to modern, AI-native architectures.
Qualifications
- Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- 10+ years of experience in software engineering, with at least 5 years in a Lead Architect or Engineering Manager role.
- Deep expertise in designing large-scale distributed systems and high-availability platforms.
- Proficiency in programming languages such as Python, Java, or C++, with a strong understanding of machine learning frameworks (TensorFlow, PyTorch).
- Experience with containerization (Docker, Kubernetes) and CI/CD pipelines.
- Strong knowledge of cloud architecture principles and data privacy regulations.
- Exceptional problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.