Bangalore, KA, IN, _
Live, first seen by us 30 days agoOwn the enterprise AI reference architecture for GenAI and agentic AI solutions
Select models and platforms across AWS Bedrock, Azure OpenAI and Databricks
Design multi-agent systems using LangGraph, CrewAI, AutoGen and similar frameworks
Build enterprise RAG solutions with embeddings, hybrid search and vector databases
Lead architecture reviews and set engineering and security standards for AI delivery
Own and lead the enterprise AI reference architecture and end-to-end design for Generative AI and Agentic AI solutions
Select the optimal models, platforms, and architectural patterns across AWS Bedrock, Azure OpenAI, and Databricks
Design and implement multi-agent systems using frameworks such as LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel, and Amazon Bedrock Agents
Build enterprise-grade RAG solutions leveraging chunking strategies, embeddings, hybrid search, semantic search, re-ranking, and vector databases
Lead architecture reviews and establish engineering, security, and coding standards for AI solution delivery
7+ years of experience in Data Science, Machine Learning, or AI Engineering, including 3+ years architecting production GenAI/LLM solutions.
Experience with LLM fine-tuning (LoRA/PEFT) and evaluation frameworks.
Proven experience designing and deploying Agentic AI or Multi-Agent systems.
Experience with engineering data domains (BOM, PDM, SAP) or financial risk modeling (Credit Risk, IFRS 9).
Hands-on experience with at least two of AWS Bedrock, Azure OpenAI, and Databricks.
Strong expertise in Python, SQL, and PySpark with solid ML and statistical fundamentals.
TE Connectivity plc (NYSE: TEL) is a global industrial technology leader creating a safer, sustainable, productive, and connected future.
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- Hands-on experience with at least two of AWS Bedrock, Azure OpenAI, and Databricks. - Strong expertise in Python, SQL, and PySpark with solid ML and statistical fundamentals. - Experience deploying AI solutions using FastAPI, Docker, Kubernetes, and CI/CD pipelines.
Job Overview Lead the architecture, design and deployment of Generative AI, Agentic AI, ML and deep learning solutions end to end: data pipelines, retrieval, agent orchestration, model serving, evaluation and monitoring on AWS Bedrock, Azure OpenAI and Databricks. Roles & Responsibility:
- Own and lead the enterprise AI reference architecture and end-to-end design for Generative AI and Agentic AI solutions, covering data ingestion, retrieval, orchestration, model serving, security, and monitoring. - Select the optimal models, platforms, and architectural patterns across AWS Bedrock, Azure OpenAI, and Databricks, balancing accuracy, latency, scalability, cost, and compliance requirements. - Develop architecture blueprints, reference designs, and technical decision records (TDRs).
- Proven experience designing and deploying Agentic AI or Multi-Agent systems. - Hands-on experience with at least two of AWS Bedrock, Azure OpenAI, and Databricks. - Strong expertise in Python, SQL, and PySpark with solid ML and statistical fundamentals.
- Experience with engineering data domains (BOM, PDM, SAP) or financial risk modeling (Credit Risk, IFRS 9). - Certifications such as AWS Certified Machine Learning, Azure AI Engineer Associate, or Databricks Generative AI Engineer. Competencies
- Develop machine learning and deep learning solutions for forecasting, classification, anomaly detection, optimization, NLP, and predictive analytics. - Build scalable data and feature engineering pipelines using Databricks, PySpark, Delta Lake, Unity Catalog, and MLflow. - Deploy AI models and intelligent agents as scalable APIs using FastAPI, Docker, Kubernetes, and CI/CD pipelines.
- Build scalable data and feature engineering pipelines using Databricks, PySpark, Delta Lake, Unity Catalog, and MLflow. - Deploy AI models and intelligent agents as scalable APIs using FastAPI, Docker, Kubernetes, and CI/CD pipelines. Qualifications
- Strong expertise in Python, SQL, and PySpark with solid ML and statistical fundamentals. - Experience deploying AI solutions using FastAPI, Docker, Kubernetes, and CI/CD pipelines. Good to Have
- Exposure to Knowledge Graphs, Document AI, OCR, or Computer Vision. - Experience with engineering data domains (BOM, PDM, SAP) or financial risk modeling (Credit Risk, IFRS 9). - Certifications such as AWS Certified Machine Learning, Azure AI Engineer Associate, or Databricks Generative AI Engineer.
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New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.
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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.
At TE, you will unleash your potential working with people from diverse backgrounds and industries to create a safer, sustainable and more connected world.
Lead the architecture, design and deployment of Generative AI, Agentic AI, ML and deep learning solutions end to end: data pipelines, retrieval, agent orchestration, model serving, evaluation and monitoring on AWS Bedrock, Azure OpenAI and Databricks.
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, _
- Design and implement multi-agent systems using frameworks such as LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel, and Amazon Bedrock Agents. - Build enterprise-grade RAG solutions leveraging chunking strategies, embeddings, hybrid search, semantic search, re-ranking, and vector databases. - Implement prompt engineering, guardrails, structured outputs, tool/function calling, and Model Context Protocol (MCP) integrations.
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