General Summary

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 cutting-edge 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:
- Bachelors/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.
- Fast learner with a strong technical foundation and ability to work independently.
- Very Strong Analytical and problem Solving Skill.

Preferred Qualifications:
- Proficiency in data analysis using Python libraries (e.g., Pandas, NumPy, Matplotlib).
- Familiarity with SQL databases, ETL frameworks, and cloud platforms (e.g., AWS).
- Hands-on experience on Cloud Scale Distributed Computing Architectures.
- Hands-on experience with AI/ML technologies including:

- Supervised and unsupervised learning
- LLMs, GenAI platforms, and RAG optimization
- ML frameworks like scikit-learn, PyTorch, TensorFlow
- LLM integration frameworks (e.g., LangChain)

📌 Lead Architect - AI Platforms & Distributed Systems (Bengaluru)
🏢 Qualcomm
📍 Bengaluru