Job Description
Quantum Leap Dynamics is at the forefront of future technology, pioneering the architectural frameworks that will define the industry landscape in 2026 and beyond. We are seeking a visionary Senior AI Systems Architect to lead the design and implementation of next-generation intelligent infrastructure. In this role, you will bridge the gap between theoretical AI models and scalable, high-performance production systems.
Join us in shaping the digital future of the United States.
Responsibilities
- Architect Scalable AI Infrastructure: Design robust, fault-tolerant system architectures capable of handling massive data throughput and complex AI workloads.
- Lead Strategic Roadmaps: Define technical strategies for the 2026 tech stack, integrating cutting-edge machine learning models with cloud-native solutions.
- Optimize Performance: Identify bottlenecks in current systems and implement optimizations to ensure low-latency, high-efficiency processing.
- Technical Leadership: Mentor a team of senior engineers and developers, fostering a culture of innovation and technical excellence.
- Collaborate Across Disciplines: Work closely with product managers, data scientists, and security experts to align technical solutions with business goals.
- Future-Proofing: Research and prototype emerging technologies (e.g., neuromorphic computing, advanced LLMs) to prepare our infrastructure for future demands.
Qualifications
- Experience: 8+ years of experience in software architecture, with at least 3 years specifically focused on AI/ML system design.
- Technical Skills: Deep proficiency in Python, Go, or Rust, with hands-on experience with TensorFlow, PyTorch, or similar frameworks.
- Cloud Mastery: Expert-level knowledge of AWS, Google Cloud Platform, or Azure, including serverless and containerized environments.
- System Design: Proven track record of designing distributed systems at scale, including microservices and event-driven architectures.
- Communication: Exceptional ability to articulate complex technical concepts to non-technical stakeholders and leadership.
- Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field.