Data Engineering
Design and scale RAG pipelines for enterprise AI reasoning systems
As an AI Data Engineer at Kyndryl, you will architect high-performance data infrastructure for autonomous systems, focusing on Retrieval-Augmented Generation (RAG) pipelines that transform unstructured IT logs and documentation into optimized vector embeddings. You will scale vector databases like Pinecone, Milvus, or Weaviate to ensure sub-second retrieval speeds for agentic AI reasoning loops. You will also build semantic layers, knowledge g...
Why This Role?
Gain trust, autonomy, and teamwork to help define the future of AI-powered enterprise systems
Key Responsibilities
- Design and scale pipelines for Retrieval-Augmented Generation (RAG) from unstructured IT logs and documentation
- Manage health and performance of vector databases (e.g., Pinecone, Milvus, Weaviate) for sub-second retrieval
- Build knowledge graphs and semantic layers to provide context for AI agents
- Create automated data guardrails to detect noise, bias, or PII before model ingestion
- Develop, deploy, and maintain CI/CD pipelines for data infrastructure with software engineering rigor
Requirements
- Expertise in data mining, data storage, and ETL processes
- Experience developing data pipelines using tools such as Glue, Databricks, Synapse, or Datapro
Required Skills
Indonesia Context
- Working Hours Overlap:
- Flexible — work your own hours
Keywords
View Original Description from The Muse
Original description from The Muse
Who We Are At Kyndryl, we run and reimagine the mission-critical technology systems that drive advantage for the world's leading businesses. We are at the heart of progress; with proven expertise and a continuous flow of AI-powered insight, enabling smarter decisions, faster innovation, and a lasting competitive edge. For our people-Kyndryls-that means doing purposeful work that powers human progress. Join us and experience a flexible, supportive environment where your well-being is prioritized and your potential can thrive. The Role Your role As an AI Data Engineer at Kyndryl, you'll be the architect behind the high-performance data infrastructure that powers our autonomous systems. We aren't just moving tables; we're building the real-time pipelines that allow agentic AI to reason over the world's most complex enterprise environments. Join Kyndryl and gain the trust, autonomy and teamwork to help define what comes next. What you will do Orchestrate Intelligence • Architect for RAG: You'll design and scale the pipelines for Retrieval-Augmented Generation (RAG), transforming massive volumes of unstructured IT logs and documentation into optimized Vector Embeddings. • Scale vector infrastructure: You will be responsible for the health and performance of our vector databases (e.g., Pinecone, Milvus, or Weaviate), ensuring sub-second retrieval speeds for agentic reasoning loops. Master Data Transformation • Engineer semantic layers: Move beyond simple ETL to build knowledge graphs and semantic layers that provide agents with the necessary context to navigate complex infrastructure puzzles. • Automate data excellence: Using a keen eye for detail, you'll build automated data guardrails to detect noise, bias, or PII (Personally Identifiable Information) before it reaches the model, ensuring our AI remains safe and impactful. Own the Backbone • Solve meaningful challenges: Serve as the bridge between raw, messy data sources and deep technical AI work, identifying and resolving quality issues at the source. • Progress to production: With a well-defined methodology and software engineering prowess, you will build, deploy, and maintain the CI/CD pipelines for our data infrastructure, ensuring that our context window remains fresh and reliable. Who You Are Required skills and experience • Expertise in data mining, data storage and Extract-Transform-Load (ETL) processes • Experience in data pipelines development and tooling, e.g., Glue, Databricks, Synapse, or Dataproc • Experience with both relational and NoSQL databases, PostgreSQL, DB2, MongoDB • Excellent problem-solving, analytical, and critical thinking skills • Ability to manage multiple projects simultaneously, while maintaining a high level of attention to detail • Ability to communicate with both technical and non-technical colleagues, to derive and translate technical requirements from business needs Preferred skills and experience • Experience working as a Data Engineer and/or in cloud modernization • Experience in Data Modelling, to create conceptual model of how data is connected and how it will be used in business processes • Professional certification, e.g. Open Certified Technical Specialist with Data Engineering Specialization • Cloud platform certification, e.g. AWS Certified Data Analytics - Specialty, Elastic Certified Engineer, Google Cloud Professional Data Engineer, or Microsoft Certified: Azure Data Engineer Associate • Understanding of social coding and Integrated Development Environments, e.g. GitHub and Visual Studio • Degree in a scientific discipline, such as Computer Science, Software Engineering, or Information Technology Being You The "Kyn" in Kyndryl means kinship, which represents the strong bonds we have with each other, our customers and our communities. We focus on ensuring all Kyndryls feel included and we welcome people of all cultures, backgrounds, and experiences. Even if you don't meet every requirement, we encourage you to apply. We believe in g
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Frequently asked questions
- Is Data Engineering at Kyndryl a remote job?
- Yes. Data Engineering at Kyndryl is a fully remote role open to candidates worldwide.
- What type of employment is Data Engineering at Kyndryl?
- This is a full time position.
- How do I apply?
- Click the "Apply" button on this page to go to the official application at Kyndryl.
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