Staff Salesforce MuleSoft IDP Developer

ZOLL Medical Corporation•Pittsburgh, PA

7d•$100,000 - $135,000•Hybrid

About The Position

The MuleSoft & IDP Developer is a key member of the IT Applications team, responsible for designing, scaling, and maintaining automated document processing solutions using MuleSoft Intelligent Document Processing (IDP), Generative AI (GenAI), and the Anypoint Platform. This role focuses on optimizing AI prompts, architecting high-throughput document processing pipelines capable of handling millions of documents, and providing Tier 3 production support for mission-critical document extraction workflows.

Requirements

Bachelor’s degree in Computer Science, Information Systems, or a related field (or equivalent practical experience).
5+ years of hands-on experience in Salesforce administration or development tasks.
3+ years of MuleSoft integration experience, with 1+ years deploying GenAI prompt engineering or IDP workloads.
MuleSoft Certified Developer - Level 1 required.
Practical skills in structural prompt formatting (e.g., few-shot prompting, system instructions) specifically for JSON text parsing.
Proven background managing multi-worker CloudHub architectures, persistent queues, or MuleSoft RPA parallel executions.

Nice To Haves

Salesforce Certified MuleSoft Hyperautomation Developer strongly preferred.

Responsibilities

Create and manage custom document actions, schemas, and AI prompts inside the MuleSoft IDP console.
Publish IDP document actions to Anypoint Exchange as REST APIs to allow seamless consumption by Mule applications or RPA bots.
Implement human-in-the-loop review queues by establishing confidence score thresholds for automated vs. manual data validation.
Integrate extracted data payloads using DataWeave, connecting document inputs to target Enterprise Applications such as ERP, CRM (Salesforce), or databases.
Write and refine advanced LLM prompts within MuleSoft IDP to extract unstructured context, text summaries, and complex line-item tables.
Build benchmark datasets to evaluate extraction accuracy, tuning prompts to eliminate AI hallucinations and false positives.
Evaluate and configure foundational LLM models and document classifiers tailored to varying document types.
Architect asynchronous processing queues and concurrency limits to handle sudden spikes in monthly document volumes.
Manage Mule vCore allocations, rate limiting, and caching strategies to ensure cost-effective API performance on CloudHub.
Resolve complex runtime failures, expired OAuth tokens, and parsing errors blocking production queues.
Continuously adjust confidence score thresholds based on support ticket trends to balance automation rates with data accuracy.