Lead Architect – AI Platforms & Distributed Systems

Company:

Job Area:

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 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.

• 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)

Minimum Qualifications:

OR

Master's degree in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 3+ years of Hardware Engineering or related work experience.

OR

PhD in Computer Science, Electrical/Electronics Engineering, Engineering, or related field and 2+ years of Hardware Engineering or related work experience.

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