Job Description
The Opportunity
We are building the infrastructure for the future. Apex Future Tech is seeking a visionary Senior AI Architect: Project 2026 to lead the design and deployment of next-generation artificial intelligence systems. As we look toward the horizon of 2026 and beyond, we need an expert who can bridge the gap between theoretical AI research and scalable, production-grade software.
In this role, you will define the technical roadmap for our proprietary neural networks, ensuring our platforms are resilient, scalable, and ready for the demands of the future.
Why You'll Thrive Here
- Impactful Work: Build the core AI engines that will power the next decade of digital transformation.
- Future-Ready Stack: Work with the latest in Generative AI, Quantum-ready algorithms, and Edge Computing.
- Elite Team: Collaborate with Ph.D.-level researchers and industry veterans.
Responsibilities
- Architect and maintain the core infrastructure for Project 2026, ensuring 99.99% uptime and low-latency performance.
- Lead the research and integration of state-of-the-art Machine Learning models, specifically focusing on Large Language Models (LLMs) and Computer Vision.
- Define technical standards and best practices for AI development within the organization.
- Optimize system performance and scalability to handle petabyte-scale data processing.
- Partner with product managers to translate business requirements into robust technical solutions.
- Conduct code reviews, technical architecture reviews, and mentorship for junior engineers and data scientists.
Qualifications
- 10+ years of experience in software engineering, with at least 5 years specifically in AI/ML architecture.
- Master’s degree or Ph.D. in Computer Science, Artificial Intelligence, or a related technical field.
- Expert proficiency in Python, C++, and deep learning frameworks (TensorFlow, PyTorch).
- Extensive experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Proven track record of deploying AI models at scale in production environments.
- Strong understanding of data pipelines, ETL processes, and real-time data streaming.