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 design and verification 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 productionaization 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 and Skills)

• Typically requires 10+ years of progressive, hands-on software engineering experience, including technical leadership of complex, production-scale systems and broad impact across multiple teams or product areas.
• Deep proficiency in one or more modern programming languages, such as Python, Java, C++, JavaScript, or TypeScript, with extensive experience in software architecture, debugging, automated testing, performance optimization, and maintainable code design.
• Demonstrated expertise in designing, building, deploying, and operating distributed software platforms across multiple layers of the application stack, including user-facing applications, APIs, backend services, data systems, workflow systems, and infrastructure.
• Strong knowledge of distributed systems, API design, data modeling, asynchronous processing, messaging, system integration, fault tolerance, security, reliability, and production operations.
• Experience deploying and operating production workloads in at least one major cloud platform, such as AWS, Microsoft Azure, or Google Cloud Platform, with practical knowledge of networking, compute, storage, identity, security, and managed services.
• Experience with containerized applications, Kubernetes or comparable orchestration platforms, CI/CD, infrastructure as code, configuration management, environment promotion, monitoring, and incident response.
• Experience designing secure multi-user systems, including identity and access management, authorization, secrets and credential management, workload isolation, audit logs, and operational controls.
• Experience integrating AI/ML services, LLM APIs, intelligent automation, or other nondeterministic components into production software systems. Expertise in training foundation models is not required.
• Experience defining technical direction and leading cross-functional teams through architecture, implementation, deployment, migration, and continuous improvement of complex products.
• Exceptional written and verbal communication skills, with a proven ability to document and present technical designs, decisions, risks, tradeoffs, and roadmaps to technical and nontechnical stakeholders.
• Track record of independent, high-impact contributions that improve product capabilities, engineering velocity, system reliability, platform reuse, or organizational effectiveness.

Education Requirements

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, or a related technical field. A master's degree in Computer Engineering, Computer Science, Data Science, Electrical Engineering, or a related technical field is preferred.

Work Environment

This job operates in a professional office environment. This role routinely uses standard office equipment.

Physical Demands

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. While performing the duties of this job, the employee is regularly required to talk or hear. The employee frequently is required to stand; walk; use hands to finger, handle or feel; and reach with hands and arms. Specific vision abilities required by this job include close vision, distance vision, color vision, peripheral vision, depth perception and ability to adjust focus. This position requires the ability to occasionally lift office products and supplies, up to 20 pounds.

USD 208,851.58 - 271,522.09 per year

Note: The Peregrine Semiconductor name, Peregrine Semiconductor logo and UltraCMOS are registered trademarks and the pSemi name, pSemi logo, HaRP and DuNE are trademarks of pSemi Corporation in the U.S. and other countries. All other trademarks are the property of their respective companies. pSemi products are protected under one or more of the following U.S. Patents: http://patents.psemi.com

Additional Position Information: