Job Description
Shape the future of technology at QuantumLeap Dynamics, where innovation meets impact. We're seeking a visionary AI Systems Architect 2026 to spearhead next-generation autonomous systems that will redefine industries by 2026. Join our elite team of pioneers in Austin's thriving tech ecosystem, where you'll architect scalable AI frameworks powering quantum computing integration, edge AI deployment, and ethical autonomous decision-making.
This role demands a blend of strategic foresight and technical brilliance. You'll lead cross-disciplinary initiatives, architecting AI solutions that process petabytes of real-time data while maintaining enterprise-grade security and ethical compliance. Our engineers operate at the intersection of neuroscience-inspired computing and distributed systems, creating solutions that adapt and evolve autonomously.
QuantumLeap offers unparalleled growth opportunities, competitive equity packages, and the chance to work on projects that will literally shape human progress. If you're driven to build systems that learn, adapt, and innovate beyond current paradigms, this is your calling.
Responsibilities
- Architect scalable AI frameworks processing 10M+ data points/sec with <0.1ms latency
- Design quantum-classical hybrid systems for autonomous decision-making at edge/IoT scale
- Lead implementation of ethical AI governance frameworks ensuring bias-free outcomes
- Develop adaptive neural networks with continuous learning capabilities
- Optimize AI pipelines for multi-cloud and hybrid quantum environments
- Establish AI observability systems for real-time performance monitoring
- Mentor cross-functional teams in AI-first development methodologies
Qualifications
- MS/PhD in Computer Science, AI, or related field with 5+ years systems architecture
- Expertise in distributed ML frameworks (TensorFlow, PyTorch, JAX)
- Proven experience designing quantum-classical hybrid computing systems
- Deep knowledge of ethical AI frameworks and bias mitigation techniques
- Proficiency in low-latency data pipelines (Kafka, Flink, Spark)
- Published research in AI scalability or autonomous systems preferred
- Strong background in cloud-native architectures (AWS/GCP/Azure)