Agentic AI Intern (Hybrid) - Able to Commit 5 - 6 Months

TE Connectivity; Singapore; Sur place; SGD 20 000 - 27 000; Plein temps

Résumé du poste

TE Connectivity is seeking an Agentic AI Intern to join our Corporate R&D Center in Singapore. You will design and build agentic AI systems, run experiments, and contribute to a platform used by TE engineers worldwide.

You will collaborate with AI scientists, business unit partners, and local universities to embed AI into TE’s design workflows, applying prompt engineering, RAG, and multi-agent coordination to real engineering problems.

Qualifications

• Pursuing Bachelor’s or Master’s in a technical field.
• Strong Python programming skills.
• Solid understanding of LLMs and agentic AI concepts.
• Experience with at least one agentic/LLM framework through coursework, projects or open-source work.

Responsabilités

• Design, implement, and evaluate agentic AI workflows using orchestration frameworks (LangChain, LlamaIndex, AutoGen, CrewAI) for engineering use cases.
• Build and test multi-agent systems with tool-use, RAG, memory management, and multi-step planning for complex tasks.
• Develop and integrate RAG pipelines with vector databases (FAISS, Chroma, Weaviate) for semantic search over technical data.
• Benchmark state-of-the-art LLMs for engineering tasks using structured evaluation methods.
• Apply prompt engineering techniques to improve agent performance and output quality.
• Write clean, well-documented Python code and follow Git workflows.
• Assist with deploying AI agents into cloud environments (AWS, Azure, GCP) and onboard basic MLOps practices.
• Contribute to internal docs, demos, and knowledge-sharing sessions across TE.
• Support validation of AI outputs and knowledge transfer with local research institutes.

Connaissances

Python programming

LLMs basics

Agentic AI

Experiment design

Git/version control

Cloud platforms

Formation

Bachelors or Masters in CS/AI/DS/SE

Outils

LangChain

LlamaIndex

AutoGen

CrewAI

PyTorch

Hugging Face Transformers

Description du poste

At TE, you will unleash your potential working with people from diverse backgrounds and industries to create a safer, sustainable and more connected world.

Job Overview

Tyco Electronics Singapore Pte Ltd (TE Connectivity) is looking for a technically strong and motivated Agentic AI Intern to join our Corporate R&D Center. You will be embedded in a newly formed AI team that is building TE’s AI Hub in Singapore – working on real problems at the intersection of frontier AI and industrial engineering.

This is not a passive internship. You will design and build agentic AI systems, run experiments, and contribute directly to a platform used by engineers across TE’s global business units. You will collaborate with R&D scientists, business unit partners, and local university and government research centres to embed AI into TE’s design and process development workflows.

We are looking for interns who are genuinely passionate about agentic AI and software engineering – whether that passion comes from coursework, personal projects, research, or open-source contributions.

Job Responsibilities

• Design, implement, and evaluate agentic AI workflows using orchestration frameworks such as LangChain, LlamaIndex, AutoGen, or CrewAI, targeting engineering use cases in product design and manufacturing process development.
• Build and test multi-agent systems incorporating tool-use, retrieval-augmented generation (RAG), memory management, and multi-step planning to solve complex, domain-specific engineering tasks.
• Develop and integrate RAG pipelines with vector databases (e.g. FAISS, Chroma, Weaviate) to enable semantic search and knowledge retrieval over technical documents and engineering data.
• Benchmark and evaluate state-of-the‑art LLMs (e.g. GPT‑4o, Claude, Gemini, Llama, Mistral) for engineering domain tasks, applying structured evaluation methods to assess accuracy, reliability, and safety.
• Apply prompt engineering techniques – including few‑shot prompting, chain‑of‑thought, and structured output generation – to improve agent task performance and output quality.
• Write clean, well‑documented, and testable Python code; contribute to shared codebases and follow software engineering best practices including version control (Git) and code review.
• Assist with deploying and integrating AI agents into cloud environments (AWS, Azure, or GCP), working with APIs, containerisation tools, and basic MLOps practices.
• Contribute to internal documentation, technical demos, and knowledge‑sharing sessions to communicate AI platform progress to cross‑functional teams and stakeholders.
• Support validation of AI outputs and assist with knowledge transfer activities in collaboration with local Singapore research institutes and university partners.

Job Requirements

• Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related technical field.
• Solid programming skills in Python, including experience writing structured, readable, and maintainable code.
• Good understanding of large language models (LLMs) – how they work, their capabilities, and their limitations – and familiarity with 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 (e.g. LangChain, LlamaIndex, AutoGen, CrewAI) through coursework, personal projects, or open‑source contributions.
• Familiarity with software engineering fundamentals: version control (Git), modular code design, debugging, and basic testing practices. Strong analytical mindset with the ability to design experiments, interpret results, and communicate findings clearly to both technical and non‑technical audiences.
• Keen interest in R&D, a willingness to work with ambiguous problems, and the drive to learn new tools and techniques quickly.

Preferred

• Experience building RAG systems and working with vector databases such as FAISS, Chroma, Pinecone, or Weaviate.
• Familiarity with model evaluation techniques including LLM‑as‑a‑judge, RAGAS, or task‑specific benchmarking frameworks.
• Exposure to cloud platforms (AWS Bedrock, Azure OpenAI, Google Vertex AI) and tools such as Docker or basic CI/CD workflows.
• Knowledge of responsible AI practices including hallucination mitigation, output validation, agent guardrails, and safe deployment considerations.
• Experience with ML or deep learning libraries (PyTorch, Hugging Face Transformers) and an understanding of model fine‑tuning or adaptation techniques.
• Interest in or basic knowledge of engineering domains such as materials science, manufacturing processes, or product design – helpful but not essential.
• Familiarity with TE products such as connectors, cables, or sensors is a plus.

What You Will Gain

• Hands‑on experience designing and deploying real agentic AI systems in a corporate R&D environment.
• Exposure to how frontier AI is applied 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’s leading research institutes and universities.
• The chance to contribute work that directly shapes TE’s AI platform strategy and capabilities.

Values: Integrity, Accountability, Inclusion, Innovation, Teamwork