AI Compiler Architect

About the Role
We are seeking an experienced Software Architect with a strong background in designing and implementing scalable, high-performance systems. As a Software Architect you will play a key role in shaping the technical direction of our products, defining architectural best practices, and collaborating closely with cross-functional teams to deliver state-of-the-art AI-driven solutions.

This is what you are responsible for
Lead the architectural design and implementation of scalable, reliable, and high-performance software systems for AI, AI Compiler and edge computing applications.
Collaborate with product managers, software engineers, and hardware engineers to ensure alignment of technical decisions with business objectives.
Define and maintain architectural best practices, guidelines, and documentation for the software engineering team.
Evaluate and recommend technologies, frameworks, and tools to optimize the performance and scalability of our solutions.
Mentor and provide technical leadership to the engineering team, fostering a culture of collaboration and innovation.
Participate in code reviews, design discussions, and technical roadmap planning to ensure high-quality delivery.
Drive continuous improvement in system architecture and development processes to support the companys growth and evolving requirements.

Necessary qualifications
8+ years of experience in software architecture, system design, and development of scalable, distributed systems.
Proven experience in designing edge-based solutions, compilers, runtime, firmware.
Strong programming skills in modern languages such as Python, C++ or similar language.
Expertise in designing high-performance, low-latency systems for AI/ML workloads.
Strong understanding of software development methodologies, DevOps practices, and CI/CD pipelines.
Familiarity with hardware-software co-design, embedded systems, and edge computing solutions is a plus.
Excellent problem-solving and communication skills, with the ability to explain complex technical concepts to both technical and non-technical stakeholders.

Preferred qualifications
Experience with AI frameworks (e.g., TensorFlow, PyTorch) and understanding of AI/ML pipelines.
Knowledge of hardware accelerators (e.g., GPUs, NPUs) and optimization for low-power AI inferencing.
Experience working in a fast-paced, startup environment is a plus.