AI Platform and Agentic Engineer

Intel's Design Quality and Reliability organization is seeking an AI Platform Engineer to architect and build an enterprise-grade AI platform for mission-critical engineering work. This platform will enable Intel engineers to analyze complex design, qualification, and reliability data; automate engineering workflows; access organizational knowledge; and make faster, evidence-based decisions throughout the product lifecycle. The successful candidate will combine strong software engineering fundamentals with expertise in AI-native and agentic development. They will be highly proficient with Agentic AI coding assistants and able to use these tools responsibly to accelerate architecture, implementation, testing, debugging, and documentation. This role requires close collaboration with Design, Quality and Reliability, Product Engineering, Manufacturing, IT, Information Security, and other Intel stakeholders.

Responsibilities:

• Architect and develop Intel's reusable AI platform for Design Quality and Reliability.
• Build AI agents and workflows for engineering data analysis, qualification planning, risk assessment, knowledge retrieval, reporting, and process automation.
• Apply Agentic AI coding assistants to accelerate software development while maintaining rigorous engineering review and validation.
• Integrate AI capabilities with Intel engineering databases, quality-management systems, internal APIs, spreadsheets, documentation repositories, and workflow tools.
• Develop production-grade backend services, APIs, data pipelines, model gateways, and agent-orchestration components.
• Establish shared platform capabilities for identity, access control, tool authorization, memory, observability, evaluation, and auditability.
• Implement human approval, deterministic validation, and rollback controls for consequential engineering actions.
• Design evaluation frameworks using representative Intel Design Quality and Reliability use cases.
• Establish automated testing, CI/CD, secure configuration, monitoring, documentation, and operational-support practices.
• Ensure compliance with Intel requirements for intellectual-property protection, data classification, cybersecurity, privacy, and responsible AI.
• Partner with domain experts to translate engineering workflows into scalable platform capabilities.
• Mentor engineers in agentic software engineering and the responsible use of AI-assisted development tools.

Minimum Qualifications:

• Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, Data Science, or a related field.
• Significant experience in software engineering, AI engineering, platform engineering, or solution architecture.
• Advanced Python development skills and experience building production APIs and backend services.
• Demonstrated proficiency with Agentic AI coding assistants such as Claude Code, or comparable agentic software-development platforms.
• Experience developing LLM applications, AI agents, tool-calling systems, retrieval pipelines, and structured model outputs.
• Strong knowledge of software architecture, data modeling, design patterns, automated testing, version control, and code review.
• Experience with CI/CD, logging, monitoring, secrets management, access control, and production operations.
• Ability to design secure, reliable, scalable, and maintainable enterprise systems.
• Strong written and verbal communication skills, including the ability to collaborate with multidisciplinary engineering teams.

Preferred Qualifications:

• Master's degree in a relevant engineering or computer science discipline.
• Experience in semiconductor design, silicon validation, product qualification, Design Quality and Reliability, failure analysis, or manufacturing.
• Familiarity with reliability topics such as device aging, electromigration, ESD, latch-up, TDDB, soft-error reliability, and high-voltage qualification.
• Experience with statistical analysis, engineering data pipelines, scientific visualization, and large engineering datasets.
• Experience integrating enterprise databases, document repositories, laboratory systems, and quality-management platforms.
• Familiarity with containers, cloud or on-premises platforms, relational databases, vector search, caching, and asynchronous processing.
• Experience with AI evaluation, prompt testing, model observability, governance, and responsible-AI controls.
• Experience building systems that require traceability, reproducibility, audit readiness, and protection of confidential intellectual property.

What Success Looks Like:

The successful candidate will establish a trusted AI foundation for Intel's Design Quality and Reliability organization-not a collection of isolated prototypes. The platform will securely scale across engineering use cases, deliver explainable and traceable results, preserve appropriate human oversight, and measurably accelerate Intel's mission-critical quality and reliability work.