Senior Staff Software Engineer, AI Platforms

Murata · San Diego

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• Senior Staff Software Engineer, AI Platforms
• Location:

San Diego, CA, US

pSemi Corporation is a Murata company driving semiconductor integration. pSemi builds on Peregrine Semiconductor’s 30-year legacy of technology advancements and strong IP portfolio but with a new mission—to enhance Murata’s world-class capabilities with high-performance semiconductors. With a strong foundation in RF integration, pSemi’s product portfolio now spans power management, connected sensors, optical transceivers, antenna tuning and RF frontends. These intelligent and efficient semiconductors enable advanced modules for smartphones, base stations, personal computers, electric vehicles, data centers, IoT devices and healthcare. From headquarters in San Diego and offices around the world, pSemi’s team explores new ways to make electronics for the connected world smaller, thinner, faster and better.

Job Summary

 As a Senior Staff Software Engineer focused on AI platforms, you will provide end-to-end technical leadership for the software systems that enable AI-assisted RFIC product development workflows. Your primary mandate will be to define and build the platform through which AI-enabled applications and intelligent agents safely interact with engineering tools, data, and computational infrastructure. You will architect scalable systems spanning user experiences, backend services, distributed workflows, engineering data, secure execution environments, and cloud or hybrid infrastructure.

This role is centered on systems engineering, platform architecture, and production-ready deployment rather than foundational model research or model training. With significant autonomy, you will establish technical direction, convert emerging prototypes into dependable multi-user products, and create reusable platform capabilities that can support multiple engineering applications. You will remain hands-on while influencing architecture across teams, reducing systemic technical risk, and driving solutions from concept through deployment, operations, and continuous improvement. This is a senior individual contributor role for an expert engineer who can help build the software foundation for next-generation semiconductor innovation, including 5G and beyond.

Roles & Responsibilities

This position has responsibility for:

• Own the architecture and evolution of distributed software platforms that support AI-enabled engineering workflows. Define service boundaries, APIs, data flows, execution models, asynchronous processing patterns, and platform standards that can be reused across multiple products and teams. Establish a multi-year technical direction while balancing near-term delivery, maintainability, security, and operational risk.
• Design and productionize systems that incorporate generative AI, LLM services, intelligent agents, retrieval, tool-driven automation, and human approval workflows. Focus on reliability, evaluation, traceability, failure handling, policy enforcement, and secure execution rather than model research or training. Create common patterns that allow new AI capabilities and engineering tools to be integrated efficiently and safely.
• Architect, implement, and maintain end-to-end software products spanning modern web applications, backend services, APIs, real-time interactions, and engineering integrations. Establish scalable design patterns that enable teams to deliver intuitive, maintainable, and reliable user experiences while remaining hands-on in critical areas of the codebase.
• Design, automate, and continuously improve development, testing, deployment, and production environments across AWS, Microsoft Azure, Google Cloud Platform, on-premises infrastructure, or hybrid environments. Establish robust practices for containerization, Kubernetes or comparable orchestration, infrastructure as code, CI/CD, configuration management, release automation, networking, storage, and environment promotion.
• Lead the development of secure, resilient, and production-ready systems with strong observability, fault tolerance, recovery, and operational support. Define standards for identity and access management, authorization, secrets and credential management, workload isolation, auditability, monitoring, incident response, root-cause analysis, and service-level objectives.
• Collaborate across software, infrastructure, AI, and RFIC engineering teams to automate workflows involving design, simulation, testbench configuration, job execution, data collection, analysis, verification, and report generation. Integrate AI-enabled capabilities with EDA tools and computational environments in ways that are safe, reproducible, traceable, and usable by engineers.
• Direct the design of data architectures and integration patterns that connect applications, databases, engineering tools, AI services, enterprise systems, and long-running computational workloads. Ensure data is reliable, secure, discoverable, and accessible, and establish resilient orchestration patterns for queued, asynchronous, and failure-prone workflows.
• Serve as a technical authority across multiple products and engineering disciplines. Lead architectural reviews, resolve complex cross-system challenges, make build-versus-buy and platform-standardization decisions, identify and retire systemic technical risk, establish engineering standards, and mentor other engineers. Drive alignment through technical judgment and influence rather than reporting authority.
• Independently investigate emerging software, cloud, AI platform, infrastructure, and developer-platform technologies. Identify practical opportunities to apply them within semiconductor engineering and produce clear architecture, design, operational, decision, and roadmap documentation that supports alignment, adoption, and long-term maintainability.

Minimum Qualifications (Experience

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