Job Description
We are looking for a visionary Senior AI Architect to spearhead the 2026 Initiative, our company's roadmap to revolutionize autonomous decision-making systems. In this pivotal role, you will design the neural infrastructure that will power our enterprise solutions for the next decade. You will work at the intersection of deep learning, distributed systems, and cloud scalability to build models that are not only accurate but also ethically sound and energy-efficient.
Why Join the 2026 Initiative?
At Apex Systems, we are not just predicting the future; we are building it. As part of the 2026 team, you will have the autonomy to experiment with bleeding-edge technologies, mentor the next generation of engineers, and directly influence the strategic direction of our AI portfolio. You will operate in a high-performance environment that values innovation, precision, and impact.
Responsibilities
- Architect and deploy scalable deep learning pipelines for the 2026 Initiative, focusing on transformer models and reinforcement learning.
- Lead the technical strategy for migrating legacy AI workloads to a microservices architecture with zero-trust security protocols.
- Collaborate with cross-functional teams including product managers, data scientists, and security experts to define technical requirements.
- Optimize model inference speed and reduce latency for real-time decision-making applications.
- Establish best practices for MLOps, ensuring reproducibility and continuous integration of AI models.
- Mentor junior architects and engineers, fostering a culture of technical excellence and continuous learning.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field.
- 8+ years of experience in software engineering, with at least 4 years specifically in AI/ML architecture.
- Proven expertise in designing large-scale distributed systems using Python, TensorFlow, or PyTorch.
- Deep understanding of cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Strong background in NLP, Computer Vision, or Multi-Agent Systems.
- Experience with ethical AI frameworks and bias mitigation in model training.