Internship - Solidworks Devops Ai

Role Description s & Responsibilities

We are looking for an intern to work at the intersection of AI and Dev Ops, focused on enhancing engineering productivity s role is centered on applying AI to improve existing release engineering systems and to build intelligent tools that assist engineers in troubleshooting, automation, and decision‑making.

You will help evolve traditional Dev Ops workflows into AI‑augmented systems—including building conversational “chat‑pod” style assistants that can analyze builds, logs, and pipelines in real time. You’ll gain hands‑on experience building AI‑powered engineering tools at enterprise scale. Some of your responsibilities include:

• Develop AI‑powered tools to analyze build logs, pipeline outputs, and system telemetry
• Implement intelligent troubleshooting assistants (chat‑based tools) for build failures, CI/CD pipeline issues, infrastructure and deployment diagnostics
• Explore LLM‑based solutions for summarizing logs, identifying root causes, and recommending fixes
• Enhance existing Dev Ops tooling
• Improve current automation systems with AI‑driven insights and optimization
• Add intelligence to logging and monitoring systems
• Build/test orchestration pipelines
• Create alerting and anomaly detection frameworks, as well as automation and productivity design solutions to reduce manual debugging and repetitive engineering tasks
• Build tools that can correlate logs across distributed systems, detect patterns in failures across builds, and recommend or auto‑trigger remediation steps

• Pursuing a Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related field
• Strong programming skills in C# (preferred), Python, Power Shell, C++, HTML and React
• Understanding of software development lifecycle and systems engineering fundamentals

• Exposure to AI/ML or LLM‑based systems (e.g., prompt engineering, NLP, model APIs)
• Exposure to Azure Dev Ops ALM
• Familiarity with Dev Ops concepts (CI/CD, build systems, automation pipelines)
• Experience working with logs, telemetry, or monitoring systems
• Knowledge of Windows Server environments and scripting
• Experience or coursework in data analysis, anomaly detection, or system diagnostics
• Prior experience in IT, Dev Ops, or infrastructure environments is a strong plus