Job Description
Are you ready to define the technological landscape of 2026 and beyond? Nexus Future Technologies is seeking a visionary Senior AI Systems Architect to spearhead our next-generation infrastructure. We are building the core AI engine that will power enterprise solutions for the future. If you have a passion for pushing the boundaries of machine learning and distributed systems, this is your opportunity to lead from the front.
As a key member of our engineering leadership team, you will be responsible for the end-to-end architecture of our proprietary AI models, ensuring they are scalable, secure, and capable of handling complex, real-world data challenges. We are looking for a strategic thinker who can bridge the gap between cutting-edge research and production-grade software engineering.
Responsibilities
- Architect Scalable Infrastructure: Design and implement distributed machine learning pipelines and microservices capable of handling petabyte-scale data.
- Model Optimization: Lead initiatives to optimize neural network inference for low-latency, high-throughput environments.
- Tech Strategy: Define the technical roadmap for AI evolution, evaluating and integrating emerging technologies to maintain a competitive edge.
- Cloud Leadership: Oversee cloud architecture on AWS/Azure, ensuring high availability, cost-efficiency, and security compliance.
- Team Mentorship: Mentor junior architects and engineers, fostering a culture of innovation and continuous learning.
- Cross-Functional Collaboration: Partner with product managers and data scientists to translate complex requirements into robust technical solutions.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- Experience: 5+ years of experience in AI engineering, with at least 2 years in a senior or lead architecture role.
- Programming: Deep expertise in Python, PyTorch, TensorFlow, or JAX.
- Systems: Strong understanding of distributed systems, containerization (Docker/Kubernetes), and cloud platforms (AWS, GCP, or Azure).
- Problem Solving: Proven track record of solving complex engineering problems and optimizing system performance.
- Leadership: Demonstrated ability to lead cross-functional teams and drive technical initiatives to completion.