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AI Software Staff Engineer

Information Technology Campbell, California

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Description

AI Software Staff Engineer

Location:

Campbell, CA

Arteris connects innovation.

Our technology helps the world's most visionary companies—from startups to Fortune 500 leaders—build smarter, faster semiconductors, specifically SoCs and chiplets. From the car you drive, to the AI in the cloud, Arteris connects the innovative tech that shapes tomorrow.

What You'll Do as a AI Software Staff Engineer at Arteris

Join our innovative team and help shape the future of semiconductor technology, specifically system-on-chip (SoC) and chiplets. In this role, you will contribute to [insert a high-level purpose or function of the role], collaborating with cross-functional teams to drive impact across cutting-edge products and solutions.

You will work at the intersection of software engineering, AI application development, and deployment infrastructure, within a technology environment focused on EDA, security, semiconductors, and SoC design.

You will collaborate with our research and development team who develop cutting edge applications of AI towards security solutions, with the objective of transforming these solutions into robust, reliable, production-ready applications and services.

This is not primarily an AI research or model-development role. We are looking for a Software Engineer with a strong understanding of AI technologies who can build the systems required to bring them into production.

You will work with applications based on LLMs, chatbots, RAG systems, AI assistants, and AI agents, while addressing the technical challenges involved in their application, integration and deployment.

Key Responsibilities

Turn AI/ML and LLM proof-of-concepts into production-grade software applications and services. Design, develop, and maintain software components surrounding AI models, including APIs, backend services, data pipelines, integrations, and user-facing applications. Develop and deploy LLM-powered applications, including chatbots, RAG systems, AI assistants, and agent-based applications. Integrate existing AI/ML models and services into broader software products and workflows. Deploy AI applications in cloud and/or on-premises environments, ensuring scalability, reliability, performance, and maintainability. Work with containerized and distributed environments and contribute to deployment automation and CI/CD pipelines. Address production engineering requirements including security, networking, authentication, authorization, monitoring, logging, observability, and resource management. Collaborate with Software, Infrastructure, Hardware, and Application teams to integrate AI capabilities into existing EDA, security, semiconductor, and SoC design workflows. Investigate and resolve production issues related to AI services, applications, deployment, performance, and integration. Contribute to software architecture and make pragmatic technical decisions that balance development speed, reliability, scalability, and maintainability. Write high-quality, maintainable, well-tested production code and contribute to engineering best practices.

What You Bring

5+ years of professional software engineering experience, with strong programming and software development skills. 3+ years experience contributing to EDA tooling or working within semiconductor engineering environments. Strong experience with technologies such as LangGraph, Docker, Kubernetes, CI/CD, REST/gRPC APIs, databases, monitoring, and logging. Strong experience with Python, C++, or similar programming languages. Experience using AI/ML models as part of software applications. Experience developing production-quality software, APIs, backend services, or distributed applications. Experience deploying software in cloud or on-premises environments. Understanding software security concepts, networking, authentication, authorization, and production deployment practices. Good understanding of software architecture, data structures, algorithms, and object-oriented design. Ability to understand and work within complex technical domains, including hardware and semiconductor technologies, with practical knowledge of EDA tooling or semiconductor design workflows. Ability to collaborate effectively with AI/ML specialists and transform experimental prototypes into robust software solutions. Bonus Points If You Have

Experience bringing an AI or LLM proof-of-concept into production.

Experience with cloud platforms such as AWS, Azure, or GCP.

Experience with LLM frameworks, vector databases, RAG architectures, or agentic systems.

Experience with semiconductor IP, interconnects, or Network-on-Chip (NoC) technologies.

Experience with commercial EDA platforms.

Experience or background in hardware security.

Education Requirements

Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, Artificial Intelligence, or a related technical field required. Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related discipline preferred. Estimated Base Salary

$165,000 to $190,000 annually. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

About Arteris

Arteris is a global leader in system IP used in semiconductors to accelerate the creation of high-performance, power-efficient silicon. Arteris network-on-chip (NoC) interconnect IP system-on-chip (SoC) integration automation software and hardware security assurance technology are used by the world's top semiconductor and technology companies to improve overall performance, engineering productivity, reduce risk, lower costs, and bring complex designs to market faster. Learn more at arteris.com.

With over 380 team members headquartered in Silicon Valley and offices around the world, we work with startups and global tech leaders alike to build the next generation of electronic products. We believe in people, purpose and impact. Join us and help shape what comes next.

Disclaimer

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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