Agentic AI Intern (Hybrid) - Able to Commit 5 - 6 Months
TE Connectivity4 hours ago
Singapore, SingaporeIntern
Responsibilities
- Design, implement, and evaluate agentic AI workflows for engineering use cases in product design and manufacturing process development.
- Build and test multi-agent systems with tool use, retrieval-augmented generation, memory management, and multi-step planning.
- Develop and integrate RAG pipelines with vector databases for semantic search over technical documents and engineering data.
- Benchmark and evaluate LLMs for engineering-domain tasks, assessing accuracy, reliability, and safety.
- Apply prompt engineering techniques such as few-shot prompting, chain-of-thought, and structured output generation.
- Write clean, documented, testable Python code and contribute to shared codebases through version control and code review.
- Assist with deploying and integrating AI agents into AWS, Azure, or GCP environments using APIs, containerization tools, and basic MLOps practices.
- Create internal documentation, technical demonstrations, and knowledge-sharing sessions for cross-functional stakeholders.
- Support AI-output validation and knowledge-transfer activities with Singapore research institutes and university partners.
Requirements
- Currently pursuing a bachelor’s or master’s degree in computer science, artificial intelligence, data science, software engineering, or a related technical field.
- Strong Python programming skills and experience writing structured, readable, and maintainable code.
- Understanding of LLMs, including their capabilities and limitations, and core agentic AI concepts such as tool use, memory, planning, and multi-agent coordination.
- Hands-on experience with at least one agentic or LLM framework through coursework, personal projects, or open-source contributions.
- Familiarity with version control, modular code design, debugging, and basic testing practices.
- Ability to design experiments, interpret results, and communicate findings to technical and non-technical audiences.
- Interest in R&D, comfort with ambiguous problems, and willingness to learn new tools and techniques quickly.
- Preferred experience with RAG systems and vector databases such as FAISS, Chroma, Pinecone, or Weaviate.
- Preferred familiarity with LLM evaluation methods including LLM-as-a-judge, RAGAS, or task-specific benchmarking frameworks.
- Preferred exposure to AWS Bedrock, Azure OpenAI, Google Vertex AI, Docker, or basic CI/CD workflows.
- Preferred knowledge of responsible AI practices, hallucination mitigation, output validation, agent guardrails, and safe deployment.
- Preferred experience with PyTorch or Hugging Face Transformers and model fine-tuning or adaptation techniques.
- Interest or basic knowledge of materials science, manufacturing processes, or product design is helpful; familiarity with TE connectors, cables, or sensors is a plus.
Benefits
- Hybrid internship requiring a 5–6 month commitment.
- Hands-on experience designing and deploying agentic AI systems in a corporate R&D environment.
- Exposure to applying frontier AI to complex industrial engineering challenges at global scale.
- Mentorship from experienced AI scientists and engineers with regular feedback and guidance.
- Opportunities to collaborate with Singapore research institutes and universities.
- Opportunity to contribute to TE’s AI platform strategy and capabilities.
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About TE Connectivity
TE Connectivity plc (NYSE: TEL) is a global industrial technology leader creating a safer, sustainable, productive and connected future. As a trusted innovation partner, our broad range of connectivity and sensor solutions enable the distribution of power, signal and data to advance next-generation transportation, energy networks, automated factories, data centers enabling artificial intelligence and more. Our more than 90,000 employees, including 10,000 engineers, work alongside customers in approximately 130 countries. In a world that is racing ahead, TE ensures that EVERY CONNECTION COUNTS.