AI Software Engineering Intern – Industrial AI Copilot; Summer Co-op

Change the future with us.

We are passionate about innovations that mean real progress. We are excited about technologies that still need to be developed. What about you? Do you want to use your curiosity, passion, and creativity to make the lives of millions of people easier and better? Join us as a graduate –either by beginning your career with us or through a co‑op placement.

Whichever path you take, we’re looking forward to seeing your perspective.

• Freedom and a healthy work‑life balance– Embrace our flexible work environment with flex hours, telecommuting and digital work spaces.
• Solve the world’s most significant problems – Be part of exciting and innovative projects.
• Engaging, challenging, and fast evolving, cutting edge technological environment.
• Opportunities to advance your career and mentorship programs on a local and global scale.
• Competitive total rewards package
• Contribute to our social responsibility initiatives focused on access to education, access to technology and sustaining communities and make a positive impact on the community.
• Participate in our celebrations, social events and offsite business events.
• Opportunities to contribute your innovative ideas and get paid for them!
• Employee perks and discounts.
• Diversity and inclusivity focused.

Term:
May 4, 2026 – August 28, 2026

AI Engineering Intern on the Industrial AI team, you will help build and product ionize LLM‑powered capabilities for DI product technical support. You’ll work hands‑on across the GenAI stack – RAG, prompt and context design, automated evaluation, LLMOps monitoring, and data refinement – to improve groundedness, reduce hallucinations, and ensure reliable performance in an enterprise Azure environment. You’ll collaborate with engineers and domain experts to ship measurable quality improvements for English and French user queries.

You’ll also contribute to thought leadership by creating content and supporting the company’s overall GenAI strategy and adoption initiatives.

• Research and learn about various GenAI tools, platforms, and use cases relevant to Siemens' business
• Build and iterate on RAG pipelines (chunking, retrieval strategies, citation/grounding behavior) to improve answer accuracy for technical support content
• Develop and maintain prompt/context templates and lightweight guardrails to increase consistency and reduce hallucinations
• Design and implement evaluation harnesses (golden test sets, regression tests, automated metrics) to measure quality across English and French queries; coordinate spot checks with French‑speaking SMEs
• Run structured experiments (e.g., retrieval/prompt variants) and analyze results to recommend changes based on quality, latency, and cost
• Implement LLMOps/observability: logging, dashboards, and monitoring for answer quality signals, failure modes, latency, and token/cost usage
• Integrate user feedback mechanisms (thumbs up/down, failure tagging) and close the loop with systematic improvements
• Support deployment and operations in Microsoft Azure (CI/CD, environments, secure access patterns) in collaboration with the engineering team
• Document best practices and contribute to internal enablement material (usage guidelines, prompting tips, quality playbooks)

• Currently enrolled in a Master’s program in computer science, engineering, AI, or a related technical field.
• Solid software engineering skills with experience building production‑grade code (Python preferred, plus REST APIs, Git, Docker)
• Hands‑on experience with LLMs in applied/production settings, such as building GenAI apps using RAG, tool/function calling, and prompt/context engineering
• Familiarity with LLM evaluation concepts (test sets, regression testing, groundedness/faithfulness, qualitative error analysis); experience with evaluation frameworks is a plus
• Experience with cloud development – Microsoft Azure is a strong plus (Azure AI, monitoring/logging, CI/CD)
• Strong analytical skills: able to translate ambiguous quality issues into measurable metrics and experiments
• Good communication and collaboration skills across engineering and domain stakeholders
• French is an asset…