Job Description
Are you ready to architect the technology of tomorrow? Nexus Horizon is seeking a visionary Future Tech Architect to spearhead our 2026 roadmap. In this pivotal role, you will design next-generation AI systems that will define the digital landscape for the coming decade. You won't just be building software; you will be building the future.
We are looking for a pioneer who thrives on ambiguity and possesses the technical prowess to turn futuristic concepts into production-ready reality. If you are passionate about the intersection of Artificial Intelligence, Quantum Computing, and Human-Computer Interaction, this is your chance to lead the charge.
Why Join Us?
- Shape the Future: Work on projects that are currently theoretical and bring them to life.
- Unlimited PTO: We believe in work-life balance and creative freedom.
- Equity Package: Be a part of the next unicorn.
Responsibilities
- Define and execute the architectural vision for Nexus Horizon's 2026 technology stack, focusing on Generative AI and Autonomous Systems.
- Lead the design of scalable, high-performance machine learning pipelines and data infrastructures.
- Collaborate with cross-functional teams (Product, Research, Design) to translate complex requirements into robust technical solutions.
- Stay at the forefront of AI innovation, evaluating and integrating emerging technologies like LLMs and Neuro-symbolic AI.
- Mentor senior engineers and architects, fostering a culture of technical excellence and continuous learning.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related STEM field; PhD preferred.
- 5+ years of experience in software engineering or AI architecture, with at least 2 years in a leadership or senior architect role.
- Deep expertise in Python, PyTorch, TensorFlow, and modern cloud-native architectures (AWS/GCP/Azure).
- Proven track record of deploying large-scale AI models into production environments.
- Strong understanding of Machine Learning operations (MLOps) and Data Engineering best practices.