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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer - AI & Analytics Infrastructure - **Company:** IBM - **Location:** Austin, TX, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Microsoft Azure, Continuous Integration, Data Governance, Data Infrastructure, Data Transformation, Document-Oriented Databases, Search Technologies, Enterprise Application Integration, Data Logging, Enterprise Software Applications, Data Storage Technologies, Large Language Models, Multi-Agent Systems, Microsoft Fabric, Data Lineage, Data Analytics, Operational Systems, Data Management, Machine Learning Operations, Virtual Agents, Azure Synapse Analytics, Data Pipelines, Databricks - **Published:** August 21, 2026 - **Apply:** https://dejobs.org/x/x/9D15F8D9587B4E9BA4C04D0FD7F4C69E/job/ ## About the Role * 7+ years designing, developing, and deploying scalable AI applications leveraging LLMs, RAG architectures, and agentic AI workflows. * Build and operationalize AI orchestration pipelines using frameworks such as LangChain and LangGraph. * Develop AI agents capable of tool calling, contextual retrieval, memory/state management, multi-agent coordination, and autonomous workflow execution. * Implement MCP (Model Context Protocol) integration patterns to enable secure, modular interoperability between AI agents, enterprise systems, tools, and data sources. * Support the industrialization of AI capabilities through reusable architecture patterns, standardized deployment frameworks, monitoring, testing, evaluation pipelines, and operational support models. * Develop and integrate enterprise-grade APIs, vector databases, workflow platforms, and operational systems into AI-enabled business processes. * Implement AI governance, security, logging, guardrails, and human-in-the-loop controls to support responsible and scalable AI adoption. * Contribute to CI/CD, LLMOps/MLOps, and cloud-native deployment practices supporting enterprise-scale AI delivery. Preferred technical and professional experience * Experience with agentic frameworks such as LangChain, LangGraph, AutoGen, Semantic Kernel, or CrewAI * Familiarity with vector databases (e.g., Azure AI Search, Pinecone, Weaviate) for RAG implementations * Knowledge of MLOps practices and CI/CD pipelines for AI model deployment and lifecycle management * Experience with enterprise integration patterns and connecting AI solutions to CRMs, ERPs, or data platforms ## Description We are seeking an experienced Data Engineer to support the design and scaling of data pipelines and infrastructure for a high-priority Agentic AI engagement. This role is central to the success of the program - the quality, accessibility, and governance of data directly enables the AI and analytics use cases being built. You will work alongside AI architects and engineers to ensure that the right data reaches the right systems in the right form. The client is looking for someone with strong hands-on experience across modern data platforms who can operate with confidence and deliver at pace. What You'll Do Data Pipeline Design & Development * Design, build, and maintain robust data pipelines that ingest, transform, and deliver high-quality data across the platform * Develop scalable architectures using Microsoft Fabric, Databricks, and/or Azure Synapse Analytics * Ensure pipelines are performant, reliable, and built to handle the scale and variability of enterprise data * Implement data transformation and orchestration workflows that feed AI models and analytics dashboards Data Infrastructure & Architecture * Architect and maintain the underlying data infrastructure that supports AI and analytics use cases * Define and implement data lakehouse patterns, medallion architecture, and layered data models * Collaborate with AI engineers and architects to ensure data outputs are structured and accessible for model consumption * Manage and optimize data storage, compute, and processing environments for cost and performance Data Quality & Governance * Implement data quality checks, validation frameworks, and monitoring to ensure trustworthy data outputs * Establish and enforce data governance standards including lineage tracking, cataloging, and access controls * Partner with stakeholders to document data assets and ensure discoverability across the platform. This role can be performed from anywhere in the United States ## Related Videos - [Crypto-secure Data Management with In-Database Blockchain](https://www.wearedevelopers.com/videos/632-crypto-secure-data-management-with-in-database-blockchain) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [Agentic AI - From Theory to Practice: Developing Multi-Agent AI Systems on Azure](https://www.wearedevelopers.com/videos/1532-agentic-ai-from-theory-to-practice-developing-multi-agent-ai-systems-on-azure) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Build Delightful Mobile Experiences with Kotlin, Realm, and Atlas Device Sync](https://www.wearedevelopers.com/videos/694-build-delightful-mobile-experiences-with-kotlin-realm-and-atlas-device-sync) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts)