Job Description
Are you ready to architect the future? Nexus Horizons Inc. is seeking a visionary Lead AI Architect to spearhead the development of our next-generation technology stack designed for the 2026 era. In this pivotal role, you will bridge the gap between theoretical AI models and scalable, real-world infrastructure, ensuring our solutions are not just current, but pioneering.
As a key player in our R&D division, you will define the architectural patterns that will drive our products for the next decade. We are looking for a leader who thrives in ambiguity and possesses an unyielding passion for pushing the boundaries of what is possible in machine learning and cloud computing.
Why join us?
- Future-Proof Technology: Work with cutting-edge stacks including Rust, WebGPU, and advanced LLM orchestration.
- Global Impact: Your work will directly influence the infrastructure powering millions of users worldwide.
- Competitive Compensation: Top-tier salary and equity package for a senior technical leader.
Responsibilities
- Design and implement scalable, high-performance AI architectures that support the 2026 technology roadmap.
- Lead the migration to quantum-ready protocols and edge computing solutions.
- Oversee the integration of Large Language Models (LLMs) into core product ecosystems with a focus on security and latency.
- Mentor a team of senior engineers and data scientists, fostering a culture of innovation and technical excellence.
- Collaborate with cross-functional teams (Product, Design, Engineering) to translate complex business requirements into technical blueprints.
- Conduct rigorous code reviews and architecture audits to ensure system integrity and scalability.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field (PhD preferred).
- 10+ years of experience in software engineering, with at least 5 years in a senior architectural or leadership role.
- Deep expertise in Python, Go, or Rust, with a proven track record of deploying production-grade ML systems.
- Strong understanding of distributed systems, containerization (Kubernetes/Docker), and cloud platforms (AWS/GCP).
- Experience with neural network optimization, model quantization, and hardware acceleration.
- Exceptional problem-solving skills and the ability to thrive in a fast-paced, agile environment.