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About Us
Chips are at the center of today's tech-driven world. But how we design and verify them has not fundamentally changed in decades, while their complexity and specialization have skyrocketed due to increasing performance demands from AI. We are a dynamic, fast-moving team of software developers, ML scientists, and research-minded engineers on a mission to change that.
Operating with the agility of a startup but backed by industry-leading verification technologies, we are part of the System Verification Group (SVG). Our charter is to develop state-of-the-art EDA software and hardware platforms (including Xcelium, Jasper, Palladium, Protium, and Helium) and supercharge them with cutting-edge AI, automation, and advanced data-driven workflows.
About This Role
Cadence Design Systems is the leading provider of design automation tools for electronic and intelligent systems design. The ML / Software Engineer – ChipStack SuperAgent Team will be responsible for designing, implementing, and evaluating AI agents that enhance productivity across the semiconductor design lifecycle. This engineer will contribute to the development of robust agent infrastructure, evaluation systems, and production-grade AI capabilities integrated within Cadence's electronic design automation (EDA) ecosystem.
The role focuses on building reliable, scalable agentic systems that operate within complex engineering workflows. The ideal candidate combines strong software engineering fundamentals with practical experience in ML systems and agent infrastructure, enabling deployment of high-impact AI solutions in production environments.
Responsibilities
Required Qualifications
Skills of Interest
Our Culture
Behavioral skills required:
Job ID: 150896585
Skills:
Java, Sql, Nosql, Gcp, Docker, Distributed Systems, Rest Apis, Azure, Kubernetes, Python, AWS, Multi-threading and concurrency, Event-driven systems, Microservices architecture, Large-scale data processing, CI CD pipelines, Observability tools
Skills:
Retrieval and data systems, Agent architecture, Evaluation frameworks for AI systems, Software engineering fundamentals, Infrastructure and observability, AI-assisted development workflows, LLM engineering
Skills:
.Net Core, .NET 8, Angular, React, Semantic Kernel, Next.js, IBM webMethods, agentic AI, AI ML systems, Pega, AWS cloud services, microservices architecture
Skills:
.NET, Devops, Sql Database Design, React, Angular, Kubernetes, Azure, Terraform, Docker, Restful Apis, cloud-native systems, distributed architectures, microservices deployments, automated testing frameworks
Skills:
Technical Leadership, Apis, Networking, Gcp, Distributed Systems, Containers, Azure, Kubernetes, messaging systems, architecture, cloud-native architectures, security best practices, observability, public cloud platforms
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