Job Description
We are Nexus 2026 Technologies, a pioneering firm dedicated to defining the technological landscape of the next decade. We are looking for a visionary Senior AI Architect to lead our strategic initiatives, ensuring our systems are not just ready for tomorrow, but are the architects of it.
In this pivotal role, you will bridge the gap between theoretical AI breakthroughs and scalable production infrastructure. You will be instrumental in designing the neural architectures that will power our enterprise solutions in 2026 and beyond. If you are passionate about the future of Artificial Intelligence and want to build systems that think, learn, and adapt at a human level, we want to meet you.
Why Join Us?
- Work on cutting-edge Generative AI and Large Language Models.
- Competitive compensation package with equity options.
- Flexible remote-first culture with a focus on innovation.
- Opportunity to shape the ethical standards of AI in the US.
Responsibilities
- Lead the architectural design and implementation of scalable AI/ML systems for the 2026 product roadmap.
- Research and prototype novel deep learning algorithms to enhance model accuracy and efficiency.
- Collaborate with cross-functional teams to integrate AI capabilities into core business workflows.
- Optimize cloud infrastructure (AWS/GCP) to handle high-volume data processing and model inference.
- Establish best practices for data governance, model monitoring, and AI ethics compliance.
- Mentor junior engineers and data scientists, fostering a culture of technical excellence.
- Present technical strategies and roadmaps to executive stakeholders.
Qualifications
- Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- 10+ years of experience in software engineering, with at least 5 years in AI/ML architecture.
- Expert proficiency in Python, PyTorch, TensorFlow, and SQL.
- Strong understanding of Deep Learning architectures, specifically Transformers and LLMs.
- Proven experience designing microservices and distributed systems in a cloud environment.
- Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
- Experience with MLOps tools (Docker, Kubernetes, MLflow) is highly desirable.