RCI-BDX-3091 Software Engineer/AI/Anthropic Claude AI/MCP/Azure/SalesForce/SAP/Trackwise

Remote Hours PS or est hours only Must Have • AI Engineering • Anthropic Claude AI • MCP Server Customization • Microsoft Azure Databricks • SalesForce • SAP Tahiti • Trackwise Nice To Have • Microsoft Power Business Intelligence (BI) • Speech to Text tools • Text to Speech Tools JOB DESCRIPTION • Education Master's Data engr or Computer science • 7+ Years in AI using Databricks and Medical Device REQUIRED Job Description : Responsibilities: • 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. Agentic AI for Manufacturing Intelligence • 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. Production LLM Expertise (Claude-Based) • 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. Career page link: https://talentarbor.com/job/details/138133/3/662/software-engineer-san-diego-ca-us