Job Description
The Future is Calling. FutureState 2026 is pioneering the next generation of sentient computing and autonomous systems. We are not just building software; we are architecting the infrastructure that will define the technological landscape of the decade. We are seeking a visionary Principal AI Architect to lead our R&D division in Austin, Texas.
In this role, you will bridge the gap between theoretical neural networks and scalable production environments. You will work with a world-class team of engineers, ethicists, and futurists to build models that think, learn, and adapt. If you are ready to shape the world of 2026 and beyond, this is your stage.
Why Join FutureState 2026?
- Work on cutting-edge Generative AI and Quantum-ML hybrid models.
- Competitive equity package and benefits.
- Flexible remote-first culture with a vibrant Austin hub.
- Direct access to executive leadership and rapid career progression.
Responsibilities
- Architect & Design: Spearhead the architectural design of our proprietary AI framework, focusing on scalability, latency optimization, and energy efficiency.
- R&D Leadership: Lead a team of elite data scientists in researching and implementing state-of-the-art Large Language Models (LLMs) and reinforcement learning agents.
- System Integration: Integrate complex AI models into existing enterprise infrastructure, ensuring seamless interoperability with legacy systems and cloud ecosystems.
- Performance Optimization: Continuously monitor model performance, conduct A/B testing, and implement strategies to reduce inference costs by up to 40%.
- Mentorship: Mentor junior engineers and data scientists, fostering a culture of innovation, code quality, and continuous learning.
- Strategic Roadmap: Define the long-term technical vision for the AI division, aligning R&D initiatives with company business goals.
Qualifications
- Education: Master’s or PhD degree in Computer Science, Mathematics, or a related field with a focus on Artificial Intelligence or Machine Learning.
- Experience: 8+ years of professional experience in software engineering, with at least 5 years dedicated to AI/ML architecture and model deployment.
- Technical Skills: Deep expertise in Python, PyTorch, TensorFlow, and modern MLOps tools (Docker, Kubernetes, MLflow). Experience with quantum computing libraries (Qiskit) is highly preferred.
- System Design: Proven ability to design large-scale distributed systems capable of handling petabyte-scale data processing.
- Communication: Exceptional ability to translate complex technical concepts for non-technical stakeholders and cross-functional teams.
- Problem Solving: Demonstrated track record of solving ambiguous problems with innovative, pragmatic solutions.