Job Description
Join Apex Horizon Systems as a Senior AI Architect and help define the technological landscape for the year 2026. We are not just building software; we are engineering the future of autonomous intelligence. In this pivotal role, you will lead the architecture of next-generation agentic AI systems designed to revolutionize enterprise operations.
We are seeking a visionary technologist who thrives on ambiguity and possesses the foresight to build scalable, ethical, and high-performance AI models. If you are passionate about the convergence of Deep Learning, Neural Networks, and Cloud Infrastructure, we want to hear from you.
Why join us?
- Work on cutting-edge projects that define the 2026 AI roadmap.
- Competitive compensation package with equity opportunities.
- Flexible remote-first culture with state-of-the-art equipment.
- Access to a world-class research library and compute resources.
Responsibilities
- Design and deploy scalable, fault-tolerant AI infrastructure capable of handling real-time data streams at petabyte scale.
- Lead the architectural strategy for the company's flagship 2026 Generative AI product suite.
- Collaborate with cross-functional teams (Product, Engineering, Research) to translate business requirements into robust technical solutions.
- Implement rigorous testing, validation, and monitoring frameworks to ensure model accuracy, safety, and bias mitigation.
- Mentor junior engineers and architects, fostering a culture of continuous innovation and technical excellence.
- Stay ahead of industry trends, specifically focusing on Large Language Models (LLMs) and Autonomous Agents.
Qualifications
- B.S., M.S., or Ph.D. in Computer Science, Mathematics, or a related technical field from a top-tier institution.
- 8+ years of experience in software engineering, with at least 5 years focused on Machine Learning and Artificial Intelligence.
- Deep expertise in Python, PyTorch, TensorFlow, or JAX.
- Proven track record of designing and shipping production-grade AI systems.
- Strong understanding of distributed systems, microservices, and cloud-native architectures (AWS, GCP, or Azure).
- Experience with MLOps pipelines, containerization (Docker/Kubernetes), and CI/CD practices.