Job Description
Are you ready to define the future of technology? Horizon Systems is seeking a visionary Lead AI Architect to spearhead our roadmap for 2026. In this pivotal role, you will bridge the gap between theoretical AI potential and practical, scalable implementation, ensuring we remain at the forefront of the industry.
We are not just building software; we are architecting the intelligence that will drive the next decade of enterprise growth. You will collaborate with cross-functional teams to design robust, secure, and ethical AI systems that set the standard for the industry.
Why Join Us?
- Work on cutting-edge Generative AI and Large Language Model (LLM) infrastructure.
- Competitive compensation package with performance-based bonuses.
- Flexible remote-first culture with opportunities for in-office collaboration.
- Professional development budget allocated for your continuous growth.
Responsibilities
- Design and oversee the architecture of large-scale AI systems, ensuring scalability and performance for 2026 and beyond.
- Lead the research and integration of emerging AI technologies, including Transformers, Reinforcement Learning, and Neural Architecture Search.
- Establish best practices for data privacy, ethics, and bias mitigation in AI model training.
- Mentor junior engineers and data scientists, fostering a culture of technical excellence and innovation.
- Collaborate with product managers to translate complex AI capabilities into user-centric features.
- Conduct regular code reviews and architectural audits to maintain system integrity.
- Communicate complex technical concepts to non-technical stakeholders effectively.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, or a related field (or equivalent practical experience).
- 10+ years of software engineering experience, with at least 5 years in AI/ML architecture.
- Deep expertise in Python, C++, and major deep learning frameworks (PyTorch, TensorFlow, JAX).
- Proven experience deploying and optimizing LLMs in production environments.
- Strong understanding of distributed systems, cloud infrastructure (AWS/GCP/Azure), and containerization (Docker/Kubernetes).
- Experience with MLOps tools and CI/CD pipelines for machine learning.
- Exceptional problem-solving skills and a passion for solving complex technical challenges.