Job Description
We are redefining the boundaries of artificial intelligence for the Year 2026. Apex Neural Systems is seeking a visionary Senior AI Architect to lead our Project 2026 initiative, a groundbreaking program focused on autonomous agent orchestration and neuromorphic computing infrastructures. You will not just build models; you will architect the future of intelligent decision-making systems that scale across global networks.
In this role, you will bridge the gap between theoretical AI research and production-grade deployment. You will work in a high-performance environment, collaborating with elite engineers to deploy systems that operate with zero latency and maximum security. If you are passionate about the next evolution of tech and want to leave a legacy in the 2026 landscape, this is your opportunity.
Why Join Us?
- Work on cutting-edge Agentic AI frameworks.
- Competitive equity package and performance bonuses.
- Flexible remote/hybrid policy with a premium San Francisco office.
Responsibilities
- Design and implement scalable, fault-tolerant AI infrastructure capable of handling petabyte-scale data processing for the 2026 ecosystem.
- Lead the architectural strategy for autonomous agent workflows, ensuring seamless integration with legacy systems and new IoT devices.
- Optimize deep learning inference engines to reduce latency and energy consumption in edge computing environments.
- Establish best practices for MLOps, CI/CD pipelines, and model governance within the organization.
- Collaborate with cross-functional teams to translate complex business requirements into robust technical solutions.
- Conduct rigorous code reviews and mentor junior engineers and data scientists.
Qualifications
- Master’s degree in Computer Science, Artificial Intelligence, or a related field, or equivalent practical experience.
- 8+ years of experience in software engineering, with at least 5 years specifically focused on Machine Learning and AI systems architecture.
- Deep proficiency in Python, PyTorch, TensorFlow, and experience with Rust or Go for high-performance systems.
- Extensive experience designing distributed systems using Kubernetes, Docker, and cloud platforms (AWS/GCP).
- Proven track record of deploying large-scale LLMs and generative AI models in production environments.
- Strong understanding of neural architecture search (NAS) and model compression techniques.