Job Description
The Future of Intelligence Starts Here.
We are looking for a visionary Lead AI Architect to spearhead Project 2026, our next-generation initiative designed to redefine the boundaries of artificial general intelligence. If you are passionate about pushing the envelope of machine learning, neural architectures, and scalable cloud systems, Aether Systems is the place for you.
As a key member of our elite engineering team, you will design the foundational blueprints for our AI ecosystem, ensuring stability, scalability, and ethical integrity in a rapidly evolving landscape.
Why Join Us?
- Work on cutting-edge technology that will shape the industry by 2026 and beyond.
- Competitive compensation package with equity options.
- Flexible remote-first culture with state-of-the-art equipment.
- Opportunity to mentor the next generation of AI engineers.
Responsibilities
- Architect and design the core infrastructure for Project 2026, focusing on high-performance neural networks and distributed computing.
- Lead the technical strategy for integrating quantum-ready algorithms into our existing machine learning pipelines.
- Collaborate with cross-functional teamsâincluding data scientists, security experts, and product managersâto define technical requirements.
- Mentor senior engineers and conduct code reviews to maintain the highest standards of software engineering.
- Optimize existing models for latency and throughput, ensuring real-time processing capabilities.
- Establish best practices for AI governance, data privacy, and ethical AI usage.
- Stay abreast of emerging technologies in the AI landscape to ensure our roadmap remains competitive.
Qualifications
- Masterâs or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- 10+ years of professional experience in software engineering, with at least 5 years in a leadership or architect role.
- Deep expertise in Python, Rust, and distributed systems design.
- Proven track record of deploying large-scale machine learning models into production environments.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Kubernetes, Docker).
- Strong understanding of neural network architectures, transformers, and optimization techniques.
- Exceptional problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.