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Why this grade This listing scored 45/100, which is a D. It lost the most ground on pay transparency. See the breakdown
- Description depth 20 / 20 How much the posting actually says about the work, measured in characters of real text.
- Freshness 12 / 15 How recently it was posted. Older postings are likelier to be filled or abandoned.
- Remote clarity 8 / 15 Whether "remote" means anywhere, or is quietly restricted to one country.
- Corroboration 5 / 10 Whether more than one source carries this listing.
- Role specificity 0 / 10 Whether the listing is tagged well enough to tell what the role actually is.
- Pay transparency 0 / 25 A published salary range, worth more than any other single factor because it is what a candidate cannot find out without applying.
Every figure above is arithmetic over the posting itself — its salary field, its text, its age, its tags and how many sources carry it. How the grades work →
This listing does not state a salary
$125k – $188k
That is the middle half of what comparable roles paid on this board over the last 90 days — 59 listings that did publish a figure, median $160k. It is not this employer's offer, and we have no idea what they pay. It is only what the rest of the market advertised.
Headquarters:
Summary
We are looking for a Senior Integration Engineer to build and operate integration products connecting Salesforce, SAP, and a carrier data lake. This role combines hands-on integration development with end-to-end production ownership, including API design, data mapping, testing, monitoring, troubleshooting, and recovery.
General information
This role focuses on building reliable, maintainable integrations rather than creating new point-to-point integration debt. You will work across Salesforce, SAP, and carrier data lake environments, taking ownership of integrations throughout their lifecycle—from implementation and testing through production support and continuous improvement.
Strong experience with MuleSoft or a comparable enterprise integration/API platform is expected, along with practical experience integrating with SAP and working with data lake ingestion patterns.
AI-assisted engineering is an explicit expectation for this engagement. You will use AI copilots and agents as part of your daily workflow to accelerate discovery, development, testing, documentation, and operational troubleshooting. You will remain responsible for validating and hardening AI-generated output and for all production decisions.
Tasks and Deliverables
- Design and implement MuleSoft/API integrations across Salesforce, SAP, and the carrier data lake.
- Define and maintain API contracts, field mappings, transformations, and automated tests.
- Use Data Modeler to develop and maintain accurate data mappings between systems.
- Debug and resolve production integration failures independently, including root-cause analysis and preventative improvements.
- Instrument integration pipelines with appropriate monitoring, logging, and alerting.
- Support Marketing Portfolio transition integrations while avoiding unnecessary point-to-point dependencies and new integration debt.
- Use AI tools to accelerate mapping drafts, API stubs, test generation, documentation, and error-handling boilerplate.
- Review and harden AI-generated output to ensure it meets production standards for reliability, maintainability, and quality.
- Automate replay, retry, alerting, and recovery runbooks to reduce mean time to recovery (MTTR).
- Continuously improve the reliability, observability, and operational efficiency of the integrations you own.
Required experience
- 5+ years of integration engineering experience.
- Hands-on experience with MuleSoft or an equivalent enterprise ESB/API integration platform.
- Experience integrating with SAP, including IDoc, API, and/or BAPI patterns.
- Experience with Salesforce integrations and enterprise API patterns.
- Experience with data lake ingestion and integration patterns.
- Strong understanding of API contracts, data mapping, transformations, testing, and integration architecture.
- Demonstrated experience supporting integrations in production, including monitoring, troubleshooting, alerting, retry/replay, and incident resolution.
- Ability to take ownership of production issues and drive them through diagnosis, recovery, and prevention, rather than simply handing them off to another team.
- Experience using AI copilots or agents to accelerate software engineering workflows.
- Strong engineering judgment and the ability to validate, test, and improve AI-generated code and artifacts before they reach production.
Apply for this role Opens weworkremotely.com — the link as listed; we have not yet verified it is the employer's own page
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Where this listing came from
- 18 Sep 2026 We Work Remotely first sighting
Seen on 1 board over 10 days.