AI Platform Engineering Internship

Summary

Synopsys develops high-performance silicon chips and technology that support pervasive intelligence and connected applications. The AI Platform Engineering Intern will prototype agentic developer experiences, enhance engineering tools with LLM-driven capabilities, and build reliable, observable microservices integrated with source control, CI/CD, and testing systems.

Responsibilities

• Prototype agentic developer experiences that automate high-friction SDLC tasks such as code search, change impact analysis, test selection, build failure triage, and review assistance
• Enhance existing tools with LLM-driven features using enterprise guardrails including model routing/abstraction, privacy controls, and evaluation/feedback loops
• Build and integrate microservices; containerize and deploy to on-prem and cloud environments while adding observability and reliability features
• Integrate across multiple source control systems (e.g., Git, Perforce/Helix) and large monorepos to enable seamless cross-repo workflows
• Connect with CI/CD and test systems (e.g., Jenkins, GitHub Actions) to surface actionable insights and automate development workflows
• Define success metrics; add telemetry and dashboards; present demos and outcomes to R&D leadership to showcase measurable productivity gains
• Uphold security, compliance, and data governance standards including SSO/RBAC and secrets management

Skills

• Currently pursuing a BS, MS, or PhD in Computer Science, Computer Engineering, or a related field, with the intention to return to school after the internship
• Proficiency in Python and strong scripting skills
• Understanding of SDLC and CI/CD principles; hands-on knowledge of Git
• Experience building services/APIs and working with JSON/REST or gRPC; familiarity with containers
• Demonstrated interest in AI/ML or LLM applications through coursework or projects; willingness to learn agentic frameworks and evaluation methods
• Strong problem-solving and communication skills with a product-oriented mindset
• Experience with CI/CD tools (Jenkins, GitHub Actions) and artifact systems
• Familiarity with AI tooling infrastructure (LiteLLM, langchain, Chroma/pgvector DB)
• Knowledge of security/compliance basics (OAuth/OIDC, SSO, RBAC)

Qualifications

Must Haves

• Currently pursuing a BS, MS, or PhD in Computer Science, Computer Engineering, or a related field, with the intention to return to school after the internship
• Proficiency in Python and strong scripting skills
• Understanding of SDLC and CI/CD principles; hands-on knowledge of Git
• Experience building services/APIs and working with JSON/REST or gRPC; familiarity with containers
• Demonstrated interest in AI/ML or LLM applications through coursework or projects; willingness to learn agentic frameworks and evaluation methods
• Strong problem-solving and communication skills with a product-oriented mindset

Nice to Haves

• Experience with CI/CD tools (Jenkins, GitHub Actions) and artifact systems
• Familiarity with AI tooling infrastructure (LiteLLM, langchain, Chroma/pgvector DB)
• Knowledge of security/compliance basics (OAuth/OIDC, SSO, RBAC)

Benefits

• Remote options available.
• Flexible hybrid or remote working arrangement.
• Gain hands-on experience with microservices, containers, Kubernetes, observability, and reliability engineering.
• Apply agentic workflows in mature, complex, large-scale software development environments.
• Partner with senior engineers, present to R&D leadership, and contribute ideas that drive measurable improvements to cycle time, quality, and developer satisfaction.