Senior Data Scientist

Job Overview:

At TE, data and AI are core strategic enablers of future growth. We are building a world-class Advanced Analytics capability to solve complex business challenges and drive topline growth and operational efficiency across business units.

The Data & AI teams are part of the TE Information Solutions (TEIS) organization, focused on building scalable AI-powered solutions using intelligent agents and automated workflows.

The Senior Data Scientist Agentic AI & Workflow Automation will lead the design and deployment of autonomous AI agents and orchestrated workflows, leveraging cutting-edge Generative AI and Large Language Models (LLMs) to enable enterprise-wide automation and decision intelligence.

Key Responsibilities:

Agentic AI & Automation

• Design, develop, and deploy multi-agent systems using frameworks such as AutoGen, LangGraph, CrewAI, or similar
• Build intelligent workflow orchestration systems enabling autonomous decision-making
• Implement Agent-to-Agent (A2A) communication and Model Context Protocol (MCP)
• Develop enterprise automation using OpenAPI standards
• Create self-healing, adaptive workflows to optimize business processes

Generative AI & LLM Solutions

• Design and implement advanced ML, Deep Learning, and Generative AI solutions
• Define best practices for building, testing, and deploying scalable LLM-based systems
• Deliver cloud-hosted Generative AI solutions that drive measurable business outcomes

Technical & Architecture

• Integrate RAG workflows, agent-based systems, and automation frameworks into applications
• Design architectures using Vector Databases and Knowledge Graphs
• Deploy LLMs and agents on AWS and on-prem infrastructure
• Evaluate, fine-tune, and optimize ML models and LLMs for complex use cases
• Stay current with advancements in Agentic AI, Autonomous Systems, and Generative AI

Mandatory Qualifications:

Education & Experience

• BE / Masters / PhD in Computer Science, AI, ML, or equivalent practical experience
• 5+ years of overall technical experience
• 2-3+ years hands-on experience in Generative AI and LLMs
• 1+ year experience building agentic systems or workflow automation

Agentic AI & Workflow Expertise

• Hands-on experience with AutoGen, LangGraph, CrewAI, Agency Swarm, or similar
• Strong knowledge of workflow orchestration tools (Temporal, Airflow, Prefect)
• Expertise in OpenAPI, A2A protocols, and MCP
• Experience designing multi-agent architectures (memory, planning, tool-use)
• Knowledge of agent evaluation, testing, and observability

LLM & Generative AI

• Proven experience deploying and optimizing LLMs in production
• Strong experience with LangChain and LlamaIndex (mandatory)
• Hands-on experience with Amazon Bedrock, SageMaker JumpStart, or similar platforms
• Expertise in RAG architectures, fine-tuning, and prompt engineering
• Deep understanding of Vector Databases (Pinecone, Weaviate, Milvus, ChromaDB) and Knowledge Graphs

ML / DL Foundations

• Strong expertise in NLP and Deep Learning (Transformers, BERT, GPT, T5, LSTM, CNN)
• Proficiency with TensorFlow, PyTorch, Hugging Face, scikit-learn
• Strong programming skills in Python (mandatory); exposure to JavaScript/TypeScript or Node.js
• Solid grounding in data structures, algorithms, and system design

MLOps / LLMOps

• Experience with end-to-end ML/LLMOps (pipelines, training, validation, drift, serving)
• Hands-on experience with Docker, Kubernetes, and CI/CD pipelines
• Knowledge of monitoring, logging, and observability for production AI systems

Nice to Have:

• Experience with function calling, tool-use, and external API integration
• Exposure to reinforcement learning and agent training
• Familiarity with 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