Job Description
We are seeking a visionary Lead AI Architect (2026 Vision) to drive the next generation of artificial intelligence infrastructure at Apex Horizon Systems. As we prepare to define the technological landscape of the year 2026, you will be at the forefront of deploying scalable, autonomous AI systems that redefine industry standards.
In this pivotal role, you will bridge the gap between theoretical machine learning research and production-grade engineering, ensuring our platforms are resilient, ethical, and future-proof.
Responsibilities
- Strategic Leadership: Define and execute the technical roadmap for AI initiatives, aligning engineering goals with the company's 2026 vision.
- System Architecture: Design robust, distributed AI architectures capable of handling petabyte-scale data and high-concurrency workloads.
- Model Optimization: Lead the research and deployment of advanced machine learning models, focusing on latency reduction and accuracy improvement.
- Talent Development: Mentor a team of world-class engineers and data scientists, fostering a culture of innovation and continuous learning.
- Cross-Functional Collaboration: Partner with product managers and stakeholders to translate business requirements into cutting-edge technical solutions.
- Ethical AI: Establish guidelines and frameworks to ensure AI deployment is fair, transparent, and compliant with global regulations.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related technical field; PhD preferred.
- Experience: 8+ years of experience in software engineering, with at least 4 years in a leadership role architecting AI/ML systems.
- Technical Stack: Proficiency in Python, TensorFlow, PyTorch, and cloud platforms (AWS/GCP/Azure).
- Leadership: Proven track record of managing high-performance engineering teams and delivering complex projects on time.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders.
- Problem Solving: Deep understanding of deep learning, natural language processing, or computer vision.