Implementation Engineer

present of AI; New York (NY); On-site; USD 100,000 - 160,000; Full time

Job summary

Tennr is seeking an experienced integration-focused engineer to build and test customer workflows on a platform that reads medical documents and routes referrals. You will own end-to-end delivery for healthcare accounts, debug unfamiliar systems, and coordinate with customers and internal teams in an Agile setting.

You will gain hands-on practice guiding AI-assisted coding workflows, testing under real load, and handling multiple builds concurrently while learning HL7 and FHIR data formats used

Qualifications

• Several years of hands-on integration work for enterprise customers.
• Strong testing habits and methodology.
• Ability to debug unfamiliar systems while juggling multiple builds.
• Comfort in an Agile setup and owning delivery dates.
• Clear communication with customers and internal teams.

Responsibilities

• Build and test customer workflows on the platform.
• Route referrals by reading medical documents.
• Support accounts after launch and monitor performance.
• Collaborate with customers and internal teams to ensure smooth deployments.

Skills

Integration work

Testing

Debugging

Agile

Communication

Tools

HL7

FHIR

Job description

This role is about building and testing customer workflows on a platform that reads medical documents and routes referrals, then supporting those accounts after launch. A strong candidate brings several years of hands on integration work for enterprise customers, solid testing habits, and the ability to debug unfamiliar systems while juggling multiple builds at once. Clear communication with customers and internal teams matters, along with comfort in an agile setup and owning delivery dates.

How it fits the AI era

The work sits close to AI that reads faxed referrals and routes them, so the engineer builds and checks the workflows around that automation for large health systems. AI assisted coding is part of the daily toolset, which speeds up builds but raises the bar on catching wrong output before it reaches live operations. What stays human is judgment on edge cases, testing under real load, and keeping customers informed when issues arise.

How it builds AI experience

Someone here would gain hands on practice directing coding agents through non trivial builds and spotting flawed output, since the posting treats agentic workflows as a core part of the job. They would also learn how AI document reading behaves in real referral and authorization flows at enterprise scale. Building that experience means scoping agent work carefully, testing failure scenarios, and learning healthcare data formats like HL7 and FHIR.

Worth showing

• End to end testing
• Agentic coding workflows

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About Tennr

AI trained on medical documents that reads faxed patient referrals and routes them so specialty practices stop losing patients in paperwork.