Job Description
Join NexusTech Innovations at the forefront of technological evolution as we pioneer the next generation of AI infrastructure. We're seeking a visionary AI Infrastructure Architect to design, implement, and scale resilient systems that power transformative AI solutions for 2026 and beyond. This role is critical in shaping our quantum-optimized computing environment and ensuring seamless integration of emerging technologies.
As a key member of our Future Technologies Division, you'll collaborate with world-class researchers to architect solutions that push the boundaries of what's possible. Our Austin hub offers a dynamic, innovation-driven culture where your expertise will directly impact the development of autonomous systems, advanced neural networks, and next-generation data processing frameworks.
Responsibilities
- Design and implement scalable AI infrastructure solutions supporting quantum computing integration
- Lead the development of hybrid cloud architectures for distributed machine learning workloads
- Architect secure data pipelines processing petabytes of real-time sensor and IoT data
- Optimize neural network deployment across edge-to-core computing environments
- Develop automation frameworks for infrastructure provisioning and lifecycle management
- Collaborate with AI research teams to translate cutting-edge algorithms into production-ready systems
- Establish governance frameworks for ethical AI deployment and compliance with evolving regulations
Qualifications
- Minimum 8 years in infrastructure architecture with 5+ years specializing in AI/ML environments
- Expertise in Kubernetes, Terraform, and cloud-native deployment strategies (AWS/Azure/GCP)
- Deep understanding of quantum computing principles and quantum-optimized algorithms
- Proven experience with distributed systems, microservices architecture, and container orchestration
- Strong background in data pipeline engineering (Spark, Flink, Kafka) and real-time processing
- Certification in cloud architecture (AWS/Azure/GCP) and/or relevant AI/ML credentials
- Experience with MLOps tools and CI/CD pipelines for AI model deployment
- Demonstrated ability to translate complex technical concepts into strategic roadmaps