Senior Principal AI Systems Engineer

About the role

Advantest is seeking a highly experienced Senior Principal AI Systems Engineer to architect and deliver advanced production AI capabilities. This role is for a hands-on technical leader with deep expertise in agentic AI, open-source model development, model fine-tuning, evaluation systems, and reliable AI infrastructure. The ideal candidate combines advanced AI knowledge with strong software-engineering discipline and has experience building systems that reason across multiple steps, use tools, evaluate results, recover from failures, and improve from feedback. Key Responsibilities Agentic AI Systems · Architect production-grade systems for tool-using and multi-step AI agents. · Design orchestration, planning, memory, session management, retries, timeouts, observability, and failure recovery. · Establish structured and typed interfaces between models, tools, data services, and applications. · Build controls that prevent agents from bypassing required validation and approval stages. · Develop reusable agent frameworks that support multiple products and deployment environments. Model Development and Fine-Tuning · Fine-tune open-source language models and specialized models for complex technical applications. · Apply LoRA, QLoRA, full fine-tuning, distillation, preference optimization, and related post-training methods. · Develop efficient strategies for adapting foundation models to new applications and datasets. · Evaluate tradeoffs among model quality, inference performance, deployment cost, security, and maintainability. · Build optimized models and inference profiles for constrained deployment environments. Evaluation and Quality · Define measurable standards for model accuracy, reliability, safety, and production readiness. · Build offline evaluation datasets, automated regression suites, judge systems, and promotion gates. · Develop methods for measuring confidence, consistency, tool-use accuracy, and action quality. · Establish processes for model comparison, controlled release, rollback, and continuous improvement. · Ensure model outputs remain grounded in available evidence and approved data sources. Training Data and Learning Pipelines · Design reproducible pipelines for training-data generation, cleaning, labeling, versioning, and validation. · Develop synthetic-data and preference-data strategies where appropriate. · Implement controls for data leakage, contamination, duplication, provenance, and customer isolation. · Convert expert feedback and observed outcomes into high-quality training and evaluation datasets. · Maintain traceability between datasets, experiments, model versions, and production results. AI Platform and MLOps · Build repeatable training, evaluation, and deployment workflows for multi-GPU infrastructure. · Establish model lifecycle practices, including model cards, release criteria, monitoring, and rollback. · Support secure, private, air-gapped, and customer-controlled deployment environments. · Develop observability for model behavior, tool execution, latency, cost, and failure conditions. · Partner with platform and CI/CD teams to make AI workflows repeatable, testable, and auditable. Technical Leadership · Set technical direction for a small, highly skilled AI engineering team. · Review architectures, models, training methods, and production implementation decisions. · Mentor engineers and establish durable AI engineering practices. · Work with domain experts to translate complex technical requirements into reliable AI capabilities. · Communicate technical risks, tradeoffs, progress, and recommendations to engineering and executive stakeholders. Qualifications · Extensive experience developing production AI or machine-learning systems. · Deep expertise in agentic systems, tool-using models, multi-step reasoning, orchestration, and production failure modes. · Hands-on experience fine-tuning open-source language models. · Experience with LoRA, QLoRA, full fine-tuning, distillation, or related model-adaptation methods. · Experience with preference optimization, reinforcement learning, RLHF, RLAIF, DPO, or comparable post training techniques. · Demonstrated experience building closed-loop systems that propose actions, evaluate outcomes, and improve from feedback. · Strong Python and software-architecture skills. · Experience with typed APIs, structured schemas, automated testing, and CI-compatible development practices. · Experience creating rigorous model evaluations, regression tests, and release criteria. · Experience with GPU-based model training and optimized inference. · Ability to operate at Senior Principal level, including architecture ownership, technical leadership, and ambiguous problem solving. · Strong written and verbal communication skills. Preferred Qualifications · Experience developing AI systems for complex engineering, scientific, industrial, or hardware-related applications. · Experience integrating AI models with external tools, APIs, simulators, instruments, or automation systems. · Familiarity with retrieval-augmented generation and grounded AI systems. · Experience with judge models, policy gates, approval workflows, or human-in-the-loop systems. · Experience with secure or isolated model deployment. · Familiarity with intellectual-property protection and customer-data isolation. · Experience moving research-level AI methods into reliable commercial products. · Background in semiconductor, electronic-design, manufacturing, test, or related technical industries is beneficial but not required. What Success Looks Like · Establish a stable and reusable production AI architecture. · Implement structured contracts, evaluation gates, observability, and behavioral regression testing. · Deliver measurable improvements in model and agent performance. · Define defensible model-promotion and release standards. · Build repeatable model-training and adaptation workflows. · Improve the reliability, security, and maintainability of the AI platform. · Establish engineering practices that allow future applications to reuse the core AI foundation efficiently. · Raise the technical standard for advanced AI development across the organization. Ideal Candidate Profile You are a deeply technical builder who understands both modern AI research and the realities of production software. You are comfortable working across models, data, evaluation, infrastructure, and application integration. You do not rely on demonstrations or prompt engineering alone. You know how to create measurable, reproducible, secure, and maintainable AI systems that perform reliably under real operating conditions About Advantest Advantest America Inc. is part of Advantest Corporation, the world’s largest provider of automated test equipment (ATE) for the semiconductor industry. The company designs and manufactures cutting-edge testing solutions that help semiconductor manufacturers ensure the quality and performance of their products. Advantest is known for innovation, reliability, and a strong commitment to supporting its customers and employees. Our Purpose & Values: Mission: Improve lives through advanced technologies and customer-focused innovation. Vision: Be the most trusted and valued test solution provider in the semiconductor value chain. Core Values: I- Innovation is our Lifeblood N- Number One is Our Aspiration T- Trust is our Foundation E- Empowerment is Our Motivation G- Global is our Reach R- Respect is our Heart I - Inclusion and Diversity is Our Commitment T- Teamwork is our Approach Y- Yes is Our Attitude Why Join Us At Advantest, innovation starts with people. We’re looking for curious, capable, and collaborative individuals ready to shape the future of semiconductor technology. You’ll join a global team where your ideas are valued, your growth is supported, and your work makes a real impact. We foster an integrity-centered culture, where honesty, inclusion, and respect are the foundation of everything we do. Benefits Overview * Global Bonus Program: Performance-based bonuses paid twice yearly. * 401(k) Plan: Pre-tax retirement savings with company match. * Medical, Dental & Vision: Multiple plan options including HMO, PPO, and HSA. * Income Protection: Life, disability, and accident insurance at no cost. * Flexible Spending Accounts: Healthcare and dependent care options. * Employee Assistance Program: Free support for personal and work-related issues. * Flexible Time Off: Accrual starts at hire, increases with service. * Paid Holidays: 13 company holidays annually. Salary Range Non-Bay Area Target Salary Range: $165,000 - $255,000 DOE State of California Development State of California Development (EDD): - - § 60-300.5(a)(2)(3)(4) Equal opportunity clause. Details the job posting requirements. - § 60-300.5(a)(6) Equal opportunity clause. 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