Job Description
Are you ready to architect the intelligence systems of tomorrow? FutureScale Systems is seeking a visionary Lead AI Architect to define the roadmap for our next-generation platform. In this pivotal role, you will not just use existing AI tools—you will push the boundaries of what is possible, laying the groundwork for the technological landscape of 2026 and beyond.
We are a fast-paced, innovation-driven company focused on deploying autonomous agents and next-generation Large Language Models (LLMs) at scale. You will lead a world-class team of ML engineers and researchers, ensuring our infrastructure is robust, scalable, and ethically sound.
Why Join Us?
• Work on high-impact projects that shape the future of automation.
• Competitive compensation package and equity.
• Flexible remote-first culture with a vibrant Austin HQ.
Responsibilities
- Architect Next-Gen AI Systems: Design and deploy scalable architectures for Agentic AI workflows and advanced Large Language Models.
- Research & Development: Spearhead research into cutting-edge NLP techniques, including RAG (Retrieval-Augmented Generation) and prompt engineering optimization for 2026 standards.
- Model Fine-Tuning: Oversee the fine-tuning and fine-tuning of open-source models (e.g., Llama 3, Mistral) to align with specific business verticals.
- Infrastructure Management: Lead the MLOps strategy, ensuring seamless CI/CD pipelines, containerization (Docker/K8s), and cloud-native deployment on AWS.
- Team Leadership: Mentor junior engineers and data scientists, fostering a culture of innovation, code quality, and continuous learning.
- Performance Optimization: Continuously monitor and optimize model inference latency and cost-efficiency.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related quantitative field (or equivalent practical experience).
- Technical Mastery: Deep expertise in Python, PyTorch, or TensorFlow. Proven experience building and deploying LLMs at production scale.
- System Design: Strong background in distributed systems, microservices, and cloud architecture (AWS/GCP/Azure).
- Experience: 7+ years of experience in software engineering, with at least 3 years specifically in AI/ML engineering or research.
- Problem Solving: Demonstrated ability to tackle complex, ambiguous problems and deliver innovative solutions.
- Communication: Exceptional ability to communicate technical concepts to non-technical stakeholders and executive leadership.