Job Description
We are building the cognitive infrastructure for the next decade. FutureScale Systems is seeking a visionary Chief Architect: Generative Intelligence to lead our R&D division. In this pivotal role, you will architect the next generation of multimodal AI systems, designed to bridge the gap between human intent and machine execution by the year 2026.
As we stand on the precipice of the next industrial revolution, your work will define the ethical framework and technical backbone of autonomous decision-making systems. You will not just write code; you will define the trajectory of AI evolution. Join a team of world-class engineers, ethicists, and futurists committed to pushing the boundaries of what is possible.
Why join us?
- Work on projects with a 5-year runway in the most advanced AI niche.
- Competitive compensation package with equity options.
- Top-tier benefits including remote-first flexibility.
Responsibilities
- Architect the 2026 Roadmap: Design and implement scalable, fault-tolerant Generative AI infrastructure capable of handling exabyte-scale data processing.
- Model Governance: Establish rigorous frameworks for Responsible AI, ensuring transparency, fairness, and bias mitigation in all generative models.
- Multimodal Integration: Lead the integration of Large Language Models (LLMs) with computer vision and sensor data for fully autonomous agent behavior.
- Technical Leadership: Mentor senior engineering teams, conducting code reviews, and fostering a culture of innovation and continuous learning.
- Strategic Partnerships: Collaborate with product and research teams to translate theoretical breakthroughs into production-ready applications.
- Security & Compliance: Oversee the implementation of enterprise-grade security protocols for proprietary data training sets.
Qualifications
- Foundational Expertise: 8+ years of experience in software architecture, with a minimum of 4 years specifically in Machine Learning and Deep Learning engineering.
- Technical Mastery: Proficiency in Python, PyTorch, TensorFlow, and experience with distributed computing systems (Kubernetes, Docker).
- Generative AI Focus: Deep understanding of Transformer architectures, Reinforcement Learning from Human Feedback (RLHF), and fine-tuning large language models.
- Leadership Experience: Proven track record of leading cross-functional teams in high-stakes environments.
- Ethical AI Knowledge: Strong grasp of AI ethics, regulatory landscapes (GDPR/CCPA), and safe deployment practices.
- Education: Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related field.