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
Location: , ,
Salary: 64 – 74
LinkedIn: Apply Here