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Senior Data Scientist

Reads like an AI Engineer role: building products on existing AI models.

Pay
Pay not listed
Work setting
Not stated
Employment
Not stated

What you’ll work on

Full posting
  • Design and deploy multi-agent systems and agentic applications

  • Build workflow orchestration for autonomous decision-making and task execution

  • Implement A2A and MCP protocols for agent collaboration

  • Design RAG, vector DB and knowledge graph retrieval architectures

  • Evaluate, build and fine-tune ML models and LLMs for business problems

From the employer’s posting
Design, develop, and deploy multi-agent systems and agentic applications
Build intelligent workflow orchestration systems that enable autonomous decision-making and task execution
Implement Agent-to-Agent (A2A) communication protocols and Model Context Protocol (MCP) for seamless agent collaboration
Design and implement architectural solutions for Information Retrieval using RAG, Vector DBs, and Knowledge Graphs
Evaluate, build, and fine-tune ML models and LLMs to solve complex business problems

What you’ll bring

All qualifications

Core experience

  • 8+ years of overall technical experience with 2-3+ years of hands-on experience in Generative AI and LLM technologies
  • Strong knowledge of workflow orchestration tools and patterns (Temporal, Airflow, Prefect, or similar)
  • Hands-on experience with Amazon Bedrock, SageMaker JumpStart, and other cloud-based LLM platforms
  • Proficiency with ML frameworks: TensorFlow, PyTorch, Hugging Face Transformers, scikit-learn
  • Hands-on experience in MLOps/LLMOps including data pipelines, model training/refinement, validation, drift management, and serving
  • Experience with function calling, tool use, and external API integration in agent systems
Qualification wording
8+ years of overall technical experience with 2-3+ years of hands-on experience in Generative AI and LLM technologies
Strong knowledge of workflow orchestration tools and patterns (Temporal, Airflow, Prefect, or similar)
Hands-on experience with Amazon Bedrock, SageMaker JumpStart, and other cloud-based LLM platforms
Proficiency with ML frameworks: TensorFlow, PyTorch, Hugging Face Transformers, scikit-learn
Hands-on experience in MLOps/LLMOps including data pipelines, model training/refinement, validation, drift management, and serving
Experience with function calling, tool use, and external API integration in agent systems
Education & alternatives
Education & Experience: - BE, Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or equivalent practical experience - 8+ years of overall technical experience with 2-3+ years of hands-on experience in Generative AI and LLM technologies

About TE Connectivity

TE Connectivity plc (NYSE: TEL) is a global industrial technology leader creating a safer, sustainable, productive, and connected future.

In the employer’s words · Read in context

Apply at TE Connectivity

Posting record

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Open 5 monthsWe first saw this posting 157 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records
Live
First seen by us
Jun 9, 2026157 days ago
Recorded sightings
1,361
Last seen by us
Nov 13, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 157

Up longer than most. Similar jobs usually come down between day 4 and day 77.

Well past TE Connectivity’s usual: its jobs come down by about day 45.

From 51 similar postings that came down, and 140 of TE Connectivity’s. Coming down is not always a hire.

TE Connectivity is hiring

31 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring has slowed
  • Takes jobs down at a usual pace
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • JavaScript
  • Python
  • TypeScript
  • AWS
  • Docker
  • Kubernetes
  • Neo4j
  • Prefect
  • SageMaker
  • Airflow
  • Hugging Face
  • PyTorch
  • scikit-learn
  • TensorFlow
  • Transformers
  • Node.js
Where the posting names them
- Proficiency with ML frameworks: TensorFlow, PyTorch, Hugging Face Transformers, scikit-learn - Strong programming skills in Python (required), plus JavaScript/TypeScript or Node.js - Deep understanding of data structures, algorithms, and system design patterns
- Design and implement architectural solutions for Information Retrieval using RAG, Vector DBs, and Knowledge Graphs - Work with public cloud (AWS) and on-premises infrastructure for deploying LLMs, agents, and orchestration systems - Evaluate, build, and fine-tune ML models and LLMs to solve complex business problems
- Hands-on experience in MLOps/LLMOps including data pipelines, model training/refinement, validation, drift management, and serving - Experience with containerization (Docker, Kubernetes) and CI/CD pipelines for ML systems - Knowledge of monitoring, logging, and observability tools for production AI systems
- Familiarity with semantic reasoning, planning algorithms (ReAct, Chain-of-Thought, Tree-of-Thoughts) - Experience with graph databases (Neo4j, Neptune) and ontology design - Contributions to open-source AI/ML projects
- Deep hands-on experience with agentic frameworks (AutoGen, LangGraph, CrewAI, Agency Swarm, or similar) - Strong knowledge of workflow orchestration tools and patterns (Temporal, Airflow, Prefect, or similar) - Expertise in OpenAPI standards, Agent-to-Agent (A2A) protocols, and Model Context Protocol (MCP)
- Extensive experience with LLM orchestration frameworks (LangChain, LlamaIndex required) - Hands-on experience with Amazon Bedrock, SageMaker JumpStart, and other cloud-based LLM platforms - Expertise in RAG architectures, Fine-tuning techniques, and Prompt Engineering
- Expert in NLP techniques and deep learning libraries (Transformer models, LSTM, BiLSTM, CNN, BERT, GPT, T5) - Proficiency with ML frameworks: TensorFlow, PyTorch, Hugging Face Transformers, scikit-learn - Strong programming skills in Python (required), plus JavaScript/TypeScript or Node.js

Your next step

Complete your application on careers.te.com. The employer’s form will show what is required.

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Has TE Connectivity posted this job before?

Yes. We’ve followed one other Senior Data Scientist job there since October 2026. It is still up.

  1. This jobUp 157 days so far, first seen Jun 9
  2. BengaluruStill up after 31 days, first seen Oct 14

About TE Connectivity

People
About 93,000 in 2025, up 7% from the year before.Annual report (SEC Form 10-K)
Company
Listed as TEL.
H-1B visas
17 approved for new hires in fiscal 2025.US Citizenship and Immigration Services

Demand for AI Engineer roles

New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.

Weekly new AI Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 7, the most 65, and the latest week had 65.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under AI Engineer, by the work the posting describes.

AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.

Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.

An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.

Job description

View original posting ↗


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

At TE, we strongly believe that data and AI are strategic drivers for future success. We are building a world-class advanced analytics team that will solve some of the most complex strategic problems and deliver topline growth and operational efficiencies across our business units.

The Data and AI teams at TE are part of the TE Information Solutions (TEIS) Organization, building scalable solutions with AI agents and workflow for organization.

The Senior Data Scientist - Agentic AI & Workflow Automation will spearhead the development of intelligent agent systems and orchestrated workflows. This role focuses on designing, building, and deploying autonomous AI agents that drive business automation and operational excellence through cutting-edge Generative AI and LLM technologies.

Responsibilities

Agentic AI & Automation:

  • Design, develop, and deploy multi-agent systems and agentic applications using frameworks like AutoGen, LangGraph, CrewAI, or similar
  • Build intelligent workflow orchestration systems that enable autonomous decision-making and task execution
  • Implement Agent-to-Agent (A2A) communication protocols and Model Context Protocol (MCP) for seamless agent collaboration
  • Develop automation solutions using OpenAPI standards for integration with enterprise systems
  • Create self-healing, adaptive workflows that optimize business processes autonomously

Generative AI & LLM Solutions:

  • Use ML, deep learning, and Generative AI tools to design, evangelize, and implement state-of-the-art solutions
  • Define and implement best practices for building, testing, and deploying scalable AI solutions, with a focus on generative models and LLMs using proprietary or open-source models
  • Drive successful business outcomes by designing and building cloud-hosted Generative AI solutions

Technical Implementation:

  • Work closely with internal teams to integrate RAG workflows, agent-based systems, and automation frameworks into applications
  • Design and implement architectural solutions for Information Retrieval using RAG, Vector DBs, and Knowledge Graphs
  • Work with public cloud (AWS) and on-premises infrastructure for deploying LLMs, agents, and orchestration systems
  • Evaluate, build, and fine-tune ML models and LLMs to solve complex business problems
  • Stay abreast of latest developments in agentic AI, autonomous systems, language models, and generative AI technologies

What your background should look like:

Education & Experience:

  • BE, Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or equivalent practical experience
  • 8+ years of overall technical experience with 2-3+ years of hands-on experience in Generative AI and LLM technologies
  • 1+ years of experience building agentic systems, workflow automation, or autonomous AI applications

Agentic AI & Workflow Expertise:

  • Deep hands-on experience with agentic frameworks (AutoGen, LangGraph, CrewAI, Agency Swarm, or similar)
  • Strong knowledge of workflow orchestration tools and patterns (Temporal, Airflow, Prefect, or similar)
  • Expertise in OpenAPI standards, Agent-to-Agent (A2A) protocols, and Model Context Protocol (MCP)
  • Experience designing multi-agent architectures with memory, planning, and tool-use capabilities
  • Knowledge of agent evaluation, testing frameworks, and observability patterns

LLM & Generative AI:

  • Proven track record of deploying and optimizing LLM models for inference in production environments
  • Extensive experience with LLM orchestration frameworks (LangChain, LlamaIndex required)
  • Hands-on experience with Amazon Bedrock, SageMaker JumpStart, and other cloud-based LLM platforms
  • Expertise in RAG architectures, Fine-tuning techniques, and Prompt Engineering
  • Deep understanding of Vector Databases (Pinecone, Weaviate, Milvus, ChromaDB) and Knowledge Graphs

ML/DL Foundations:

  • Expert in NLP techniques and deep learning libraries (Transformer models, LSTM, BiLSTM, CNN, BERT, GPT, T5)
  • Proficiency with ML frameworks: TensorFlow, PyTorch, Hugging Face Transformers, scikit-learn
  • Strong programming skills in Python (required), plus JavaScript/TypeScript or Node.js
  • Deep understanding of data structures, algorithms, and system design patterns

MLOps/LLMOps:

  • Hands-on experience in MLOps/LLMOps including data pipelines, model training/refinement, validation, drift management, and serving
  • Experience with containerization (Docker, Kubernetes) and CI/CD pipelines for ML systems
  • Knowledge of monitoring, logging, and observability tools for production AI systems 

Nice to Have

  • Experience with function calling, tool use, and external API integration in agent systems
  • Knowledge of reinforcement learning and agent training methodologies
  • Familiarity with semantic reasoning, planning algorithms (ReAct, Chain-of-Thought, Tree-of-Thoughts)
  • Experience with graph databases (Neo4j, Neptune) and ontology design
  • Contributions to open-source AI/ML projects
  • Publications or patents in AI/ML domain

Competencies

Values: Integrity, Accountability, Inclusion, Innovation, Teamwork

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. Learn more at www.te.com and on LinkedIn, Facebook, WeChat, Instagram and X (formerly Twitter).

 

WHAT TE CONNECTIVITY OFFERS:
We are pleased to offer you an exciting total package that can also be flexibly adapted to changing life situations - the well-being of our employees is our top priority!

•    Competitive Salary Package
•    Performance-Based Bonus Plans
•    Health and Wellness Incentives
•    Employee Stock Purchase Program
•    Community Outreach Programs / Charity Events
•    Employee Resource Group

 

IMPORTANT NOTICE REGARDING RECRUITMENT FRAUD
TE Connectivity has become aware of fraudulent recruitment activities being conducted by individuals or organizations falsely claiming to represent TE Connectivity. Please be advised that TE Connectivity never requests payment or fees from job applicants at any stage of the recruitment process. All legitimate job openings are posted exclusively on our official careers website at te.com/careers, and all email communications from our recruitment team will come only from actual email addresses ending in @te.com. If you receive any suspicious communications, we strongly advise you not to engage or provide any personal information, and to report the incident to your local authorities.

Across our global sites and business units, we put together packages of benefits that are either supported by TE itself or provided by external service providers. In principle, the benefits offered can vary from site to site.

 

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Bangalore, KA, IN, 560076

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