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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Data Engineer - **Company:** Infoorigin inc - - **Location:** New York, NY, United States (Remote available) - **Salary:** $145,600.0 - $166,400.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Microsoft Azure, Cloud Computing, Cluster Analysis, Information Engineering, Data Integrity, Data Mining, Python (Programming Language), Named Entity Recognition, Salesforce.Com, SAP (Applications), SQL Databases, Systems Integration, Technical Data Management Systems, Data Logging, Large Language Models, Apache Spark, Data Lakes, Data Analytics, Trackwise, Machine Learning Operations, Virtual Agents, Data Pipelines, Databricks - **Published:** May 17, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=f2d94a7db018f203 ## About the Role Do you have experience in Salesforce Cloud?, Production grade experience using Claude LLMs within orchestrated agent workflows, including prompt management, tool calling, structured outputs, guardrails, and audit ready logging. * Unstructured Structured Manufacturing Data Transformation * Strong expertise building AI driven data pipelines that transform unstructured medical device data (complaints, CAPAs, investigations, service notes, SOPs, PDFs, emails) into structured, analytics and review ready datasets. AI Driven Quality & Failure Data Extraction * Experience developing orchestrated AI pipelines for entity extraction, event classification, failure mode standardization, trend tagging, risk categorization, and summarization aligned to quality and manufacturing taxonomies. Core ML & Statistical Analysis for Manufacturing * Solid foundation in predictive modeling, clustering, time series analysis, anomaly detection, and statistical methods applied to manufacturing processes, defects, equipment signals, and failure trends. Manufacturing Data Platforms & Engineering * Advanced proficiency with Databricks, Spark, SQL, Delta Lake, and Python to ingest, structure, and analyze large scale manufacturing, quality, and post market data, supporting downstream analytics and AI systems. Quality, CAPA & Root Cause Analytics * Demonstrated ability to correlate complaints, NCRs, CAPAs, and service data with upstream manufacturing signals using data driven root cause and investigation approaches. Enterprise & Regulated Systems (SAP Centric) * Hands on experience integrating and analyzing data from SAP Tahiti, Salesforce, TrackWise, and QMS platforms while maintaining traceability, data integrity, and compliance in regulated environments. Must Have * AI Engineering * Anthropic Claude AI * MCP Server Customization * Microsoft Azure Databricks * SalesForce * SAP Tahiti * Trackwise ## Description * Responsible to support the BDash AI-powered data analytics platform. This individual will contribute to advance data engineering pipelines, AI agent development, and cross-functional quality analytics across different areas of the business such as quality, product engineering, reliability, field service and business strategy., Deep expertise designing and deploying agentic AI systems using agentic frameworks and orchestrators to reason across manufacturing, quality, and post market data, execute multi step analysis, self correct, and drive decisions with limited human intervention. ## Related Videos - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) - [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) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Enabling intelligent logistics automation: home-grown Industrial IoT platform at Austrian Post](https://www.wearedevelopers.com/videos/2018-enabling-intelligent-logistics-automation-home-grown-industrial-iot-platform-at-austrian-post) - [OLTP in the Lakehouse: Redefining Data for AI Workloads](https://www.wearedevelopers.com/videos/2038-oltp-in-the-lakehouse-redefining-data-for-ai-workloads) - [The Data Mesh as the end of the Datalake as we know it](https://www.wearedevelopers.com/videos/156-the-data-mesh-as-the-end-of-the-datalake-as-we-know-it) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [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) - [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) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)