Job Description
About Nexus Future Systems
We are a premier innovation hub dedicated to defining the technological landscape of the next decade. Our mission is to architect the 2026 Strategic Roadmap, focusing on next-generation artificial intelligence and scalable neural networks. We are seeking a visionary Senior AI Architect to lead our technical vision and bridge the gap between theoretical AI research and production-ready engineering.
The Role
As a Senior AI Architect, you will be at the forefront of our 2026 initiatives. You will define the technical stack that will power our global platforms, ensuring scalability, security, and cutting-edge performance. You will work closely with C-level executives and cross-functional teams to translate business goals into robust AI infrastructure.
Why Join Us?
- Be a key driver of the 2026 technological evolution.
- Competitive compensation and equity package.
- Work with state-of-the-art tools and technologies.
- Flexible, remote-first culture with HQ in Austin, TX.
Responsibilities
- Define and execute the 2026 AI Technical Roadmap in alignment with company objectives.
- Design scalable, fault-tolerant machine learning pipelines and neural network architectures.
- Lead a team of data scientists and engineers to deploy state-of-the-art models.
- Conduct code reviews and architectural reviews to ensure best practices and security compliance.
- Stay ahead of emerging trends in AI, Quantum Computing, and Edge Intelligence.
- Mentor junior staff and foster a culture of continuous innovation.
- Collaborate with product managers to translate complex requirements into technical solutions.
Qualifications
- Master’s or PhD in Computer Science, Artificial Intelligence, or a related field.
- Minimum of 8+ years of experience in software engineering and machine learning.
- Expert proficiency in Python, TensorFlow, PyTorch, and distributed systems.
- Proven experience designing and deploying large-scale ML models (e.g., NLP, Computer Vision, Recommender Systems).
- Strong understanding of cloud infrastructure (AWS, GCP, or Azure).
- Excellent problem-solving skills and ability to work in a fast-paced, high-growth environment.
- Experience with MLOps and model deployment lifecycle.