Job Description
We are pioneering the next era of intelligent systems, and we are looking for a visionary AI Systems Architect to define the 2026 roadmap.
At Nexus Future Labs, we are building the infrastructure that will power the autonomous agents of tomorrow. You will be at the intersection of cutting-edge research and scalable production engineering, tasked with solving the most complex challenges in artificial general intelligence (AGI) deployment.
The Role:
In this high-impact position, you will own the architectural vision for our flagship AI products. You will bridge the gap between theoretical models and robust, real-world applications, ensuring our systems are not only smart but also efficient, secure, and scalable.
Why Nexus Future Labs?
- Future-Proofing: Work on projects directly shaping the technology of 2026 and beyond.
- Top-Tier Talent: Collaborate with world-class engineers and researchers.
- Impact: Your code will power solutions used by millions globally.
Responsibilities
- Architectural Leadership: Design and oversee the implementation of large-scale distributed systems for AI training and inference pipelines.
- Roadmap Strategy: Define the technical vision for the 2026 release cycle, identifying emerging technologies and integration points.
- Model Deployment: Lead the transition of experimental models from research labs to production environments with zero downtime.
- Performance Optimization: Continuously optimize system latency, throughput, and energy efficiency to meet enterprise-grade standards.
- Collaboration: Partner with data scientists and product managers to translate complex requirements into technical specifications.
- Mentorship: Cultivate a high-performance engineering culture and mentor junior developers on best practices in AI engineering.
Qualifications
- Education: Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- Experience: 10+ years of software engineering experience, with at least 5 years in AI/ML system architecture.
- Technical Stack: Deep proficiency in Python, PyTorch, TensorFlow, and experience with distributed computing frameworks (Apache Spark, Ray).
- Cloud Mastery: Extensive experience designing solutions on AWS, GCP, or Azure, specifically involving Kubernetes and containerization.
- Problem Solving: Proven track record of troubleshooting complex, high-stakes production issues and delivering scalable solutions.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders and cross-functional teams.