Qualifications
Minimum Qualifications 1. Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, Data Science, or a related field. 2. Significant experience in software engineering, AI engineering, platform engineering, or solution architecture. 3. Advanced Python development skills and experience building production APIs and backend services. 4. Demonstrated proficiency with Agentic AI coding assistants such as Claude Code, or comparable agentic software-development platforms. 5. Experience developing LLM applications, AI agents, tool-calling systems, retrieval pipelines, and structured model outputs. 6. Strong knowledge of software architecture, data modeling, design patterns, automated testing, version control, and code review. 7. Experience with CI/CD, logging, monitoring, secrets management, access control, and production operations. 8. Ability to design secure, reliable, scalable, and maintainable enterprise systems. 9. Strong written and verbal communication skills, including the ability to collaborate with multidisciplinary engineering teams. Preferred Qualifications 1. Master's degree in a relevant engineering or computer science discipline. 2. Experience in semiconductor design, silicon validation, product qualification, Design Quality and Reliability, failure analysis, or manufacturing. 3. Familiarity with reliability topics such as device aging, electromigration, ESD, latch-up, TDDB, soft-error reliability, and high-voltage qualification. 4. Experience with statistical analysis, engineering data pipelines, scientific visualization, and large engineering datasets. 5. Experience integrating enterprise databases, document repositories, laboratory systems, and quality-management platforms. 6. Familiarity with containers, cloud or on-premises platforms, relational databases, vector search, caching, and asynchronous processing. 7. Experience with AI evaluation, prompt testing, model observability, governance, and responsible-AI controls. 8. 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.
Job Type
Experienced Hire
Shift
Shift 1 (India)
