Lead Architect – AI Platforms & Distributed Systems

Our team is focused on applying state-of-the-art AI and ML technologies to solve complex business problems in the chip design, qualification, and debug engineering processes. We aim to enhance engineering efficiency through intelligent automation, data-driven insights, and innovative tool development.

This role focuses on building scalable cloud-native AI applications that enhance engineering productivity. You’ll work on distributed systems, cloud platforms, and user-facing tools that integrate AI/ML capabilities into chip design and debug workflows.

Key Responsibilities

- Design and implement AI/ML applications and pipelines using LLMs, GenAI platforms, and custom models to address real-world engineering challenges.

- Build intelligent agents and user interfaces that integrate seamlessly into engineering workflows.

- Develop robust data ingestion, transformation, and analysis pipelines tailored to chip design and debug use cases.

- Build distributed computing architectures and scalable backend services.

- Design intuitive user interfaces and intelligent agents for engineering teams.

- Implement robust ETL pipelines and integrate with SQL/NoSQL databases.

- Collaborate with team leads to ensure timely delivery and high-quality solutions.

- Provide technical support and training to internal teams, helping resolve issues and improve adoption.

- Engage in cross-functional initiatives to solve technical problems across departments.

- Continuously contribute to the innovation and evolution of tools, technologies, and user experiences.

Minimum Qualifications:

- Bachelor’s/Master's degree in Computer Science with minimum 7+ years of work experience

- Very Strong in data structures, algorithms, and software design principles.

- Strong programming skills in Python and C/C++.

- Experience in building scalable software systems and solving complex technical problems.

- Experience with software architecture and design patterns.