Job Description
Are you ready to define the technological landscape of 2026? Chronos Future Systems is seeking a visionary Senior AI Architect to lead our 2026 Strategic Roadmap Initiative. We are not just building software; we are engineering the future of human-computer interaction.
In this pivotal role, you will bridge the gap between theoretical AI research and production-grade infrastructure. You will own the architectural vision for our next-generation generative AI suite, ensuring scalability, security, and performance as we prepare for the 2026 market expansion. Join a team of elite engineers pushing the boundaries of what is possible.
Why Join Us?
- Shape the 2026 Roadmap directly with executive leadership.
- Work with cutting-edge hardware and cloud-native architectures.
- Competitive equity package and comprehensive benefits.
Responsibilities
- Define the 2026 Vision: Lead the architectural strategy for our upcoming AI products, defining the technical roadmap for the next fiscal year.
- System Design: Design and implement scalable, fault-tolerant distributed systems capable of handling petabyte-scale data processing.
- Model Optimization: Oversee the deployment and fine-tuning of Large Language Models (LLMs) to ensure optimal latency and cost-efficiency.
- Technical Leadership: Mentor a team of senior engineers and data scientists, fostering a culture of innovation and technical excellence.
- Cross-Functional Collaboration: Partner with product managers and UX researchers to translate complex AI capabilities into user-centric features.
- R&D Integration: Evaluate emerging technologies (Quantum computing, Neuromorphic chips) to integrate into our 2026 infrastructure.
Qualifications
- Experience: 8+ years of experience in software engineering, with at least 4 years in AI/ML architecture and system design.
- Tech Stack: Proficiency in Python, C++, and frameworks such as PyTorch or TensorFlow.
- Architecture: Deep understanding of microservices, containerization (Docker/Kubernetes), and cloud platforms (AWS/GCP).
- Leadership: Demonstrated experience leading engineering teams through complex architectural transitions.
- Education: Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related technical field.
- Problem Solving: Proven track record of solving high-scale data challenges and optimizing algorithmic performance.