Job Description
Nexus Future Labs is pioneering the next era of intelligent infrastructure. We are looking for a visionary Senior AI Architect to spearhead our 2026 Strategic Initiative. In this role, you will define the architectural blueprint for our next-generation autonomous systems and quantum-ready data platforms.
As we prepare for the pivotal year of 2026, we are seeking a thought leader who can bridge the gap between theoretical AI capabilities and scalable enterprise solutions. You will be responsible for guiding our engineering teams toward a future-proof technology stack.
What You Will Do:
Shape the technical direction of our 2026 roadmap.
Design resilient, high-throughput systems for AI deployment.
Lead architectural reviews and mentor senior engineers.
Collaborate with product leaders to translate business needs into technical solutions.
Ensure compliance and security in AI-driven environments.
Who You Are:
5+ years of experience in AI/ML engineering and system architecture.
Proven expertise in Python, PyTorch, and distributed computing.
Experience with cloud platforms (AWS/GCP) and containerization (Docker/K8s).
Strong background in Natural Language Processing (NLP) and Computer Vision.
A passion for ethical AI and responsible innovation.
Responsibilities
- Lead the design and implementation of the 2026 AI roadmap, ensuring alignment with business goals.
- Architect scalable machine learning pipelines to handle petabyte-scale data.
- Oversee the integration of quantum-ready algorithms into legacy systems.
- Mentor and develop a high-performing team of data scientists and engineers.
- Conduct technical feasibility studies for emerging AI technologies.
- Establish best practices for code quality, testing, and deployment automation.
- Communicate complex technical concepts to non-technical stakeholders.
Qualifications
- Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- 7+ years of experience in software engineering and AI system architecture.
- Deep proficiency in Python, TensorFlow, PyTorch, and Scikit-learn.
- Experience with MLOps, CI/CD pipelines, and cloud infrastructure (AWS/GCP).
- Strong understanding of neural network optimization and hardware acceleration.
- Excellent problem-solving skills and the ability to thrive in a fast-paced startup environment.
- Excellent written and verbal communication skills.