Live opening · Posted 1 day ago
At a glance
The key details from the original listing.
About the role
Description supplied by the original job listing.
At Siemens, we help organizations transform maintenance and operations through connected insights, AI-powered technology, and intelligent asset management solutions. Our software enables customers to manage the full lifecycle of assets, facilities, and infrastructure while improving efficiency, reducing risk, and optimizing long-term investments. By connecting data, people, and processes, we empower organizations to make smarter decisions, maximize asset performance, and achieve more resilient operations.
Description
Siemens Asset Management Software (AMS) Product Operations Team is seeking a curious, motivated ProdOps AI Operations Intern to join the Product Operations team within Cloud Operations for Summer 2027. Our team is shifting from reactive, manual incident handling toward a data-driven, AI-enabled way of working, and this internship is a hands-on opportunity to help make that happen.
You will use AI tools to support root cause analysis (RCA), analyze operational processes, and recommend improvements that reduce manual effort and time to resolution for our clients. You will partner closely with ProdOps team members and work with Product, Support, and Engineering stakeholders, with guidance and mentorship throughout the internship.
This 10 week Summer Internship will last between May 2027 and August 2027.
What You’ll Learn
How enterprise SaaS and cloud production operations work.
How to apply AI to real operational challenges, from RCA to process automation.
Incident trend analysis, root cause analysis, and continuous improvement techniques.
Data visualization and operational reporting.
Presenting insights and recommendations to leadership.
Location:
This position is remotely based within the United States.
However, to facilitate onboarding and establish key relationships with the team, the successful candidate will be required to attend their first week of employment onsite in Raleigh, NC. Following onboarding, the role will be fully remote.
Qualified Applicants must be legally authorized for employment in the United States and will not require employer sponsored work authorization now or in the future for employment in the United States.
You’ll make an impact by :
AI-Assisted RCA & Incident Analysis
Use AI tools to analyze production incidents and post-incident reviews.
Identify recurring failure patterns, operational trends, and common root causes.
Draft AI-assisted RCA summaries with clear findings and recommended corrective actions.
Help track whether corrective actions reduce repeat incidents.
Process & Operations Analysis
Document and assess existing ProdOps workflows.
Recommend opportunities for AI, workflow automation, and process simplification.
Create process maps showing current-state and future-state workflows.
Assist with testing and rollout of approved process and automation improvements.
Operations Reporting & Insights
Analyze operational data related to incidents, escalations, and service performance.
Build dashboards and visualizations that track operational health and improvement initiatives.
Prepare concise, leadership-ready summaries of findings and recommendations.
AI Innovation & Proof-of-Concepts
Evaluate emerging AI use cases with ProdOps stakeholders.
Experiment with Microsoft Copilot, generative AI tools, and workflow automation platforms.
Build small proof-of-concepts that improve productivity and operational effectiveness.
Research industry best practices for AI-enabled operations.
Documentation & Knowledge Sharing
Improve RCA templates, operational documentation, and process guides.
Create reusable AI prompts and playbooks for the team.
Share findings and lessons learned with the broader Cloud Operations organization.
Apply responsible AI practices, including validation and human review of AI-generated output.
This Is How you'll win Us Over
Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Analytics, Engineering, Business Technology, or a related field.
Strong analytical and problem-solving skills, demonstrated through coursework, projects, or prior internships.
Familiarity with generative AI tools such as Microsoft Copilot or ChatGPT, through coursework, projects, or personal use.
Working knowledge of Excel or Google Sheets for organizing and analyzing data.
Good written and verbal communication skills, with the ability to explain findings clearly.
Curiosity, attention to detail, and a willingness to learn in a fast-paced environment.
Ability to work both independently and as part of a team.
You'll Thrive Even More If You Also Bring
Coursework or project experience with Python, SQL, or data visualization tools such as Power BI or Tableau.
Exposure to cloud computing concepts (AWS, Azure) through classes, certifications, or personal projects.
Basic familiarity with ticketing or project tools such as Jira or Salesforce.
Interest in IT operations, incident management, or process improvement.
Prior internship, co-op, or campus project experience involving data analysis or automation.
At Siemens, you'll have the opportunity to grow your career while helping organizations operate smarter, safer, and more sustainably. We foster a culture of innovation, collaboration, and continuous learning, where employees are empowered to make a difference every day. If you're excited about solving real-world challenges and shaping the future of asset management, we encourage you to apply.
Our Commitment to Equity and Inclusion in our Diverse Global Workforce:
We value your unique identity and perspective. We are fully committed to providing equitable opportunities and building a workplace that reflects the diversity of society, while ensuring that we attract the best talent based on qualifications, skills, and experiences. We welcome you to bring your authentic self and transform the every day with us.
Siemens maintains a Drug Free workplace in accordance with applicable law.
#AMSInternsFY27
$29 $34
Work arrangement
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