Engineering Lead - Application & AI Development

Greetings From LegacyHealth!!!

Opening for Engineering Lead - Application & AI Development

Required Skill

ROLE FUNCTION - what this person actually does

• Owns one or more applications end to end: data model, backend, front end, deployment path.

• Reports to a US-based application lead; manages 2-4 offshore BAU and junior developers.

• Spends 30-40% of their week writing and reviewing code. This is non-negotiable.

• Reviews every pull request from their team before it reaches the US reviewer.

• Raises delivery risk early and in writing, including when it contradicts a stated deadline.

MUST HAVE - candidate is not submitted without all of these

• 8+ years building production software as the primary job function.

• 3+ years hands-on Java and Spring Boot: REST APIs, JPA/Hibernate, Maven or Gradle. Strong C#/.NET may be considered as a transfer case. PHP, Node-only, or test-automation backgrounds do not substitute.

• 2+ years React for desktop and mobile web: hooks, component state, REST integration.

• Strong MSSQL: query tuning, execution plans, indexing, partitioning. Azure SQL preferred.

• Python for automation, data processing, and calling hosted AI model APIs.

• Azure in production: App Service or container hosting, Azure SQL, Azure DevOps repos and pipelines, Entra ID. Linux VM administration.

• Has directly led software developers - not QA engineers: assigns work, reviews pull requests, mentors junior staff. State team size and whether they ran performance reviews.

• Has personally written and merged application code within the last 12 months.

• Fluent written and spoken English; documents technical decisions without being asked.

• Able to work US CST/EST overlap hours as defined in Shift above.

• Two contactable client references for scalable applications delivered, per original request.

PREFERRED - strengthens the application, does not gate it

• Azure AI Foundry or equivalent hosted LLM services consumed via API.

• Retrieval-augmented generation, prompt engineering, evaluating model output against a ground-truth set.

• Optimising AI workloads and databases for throughput and cost, with measurable results.

• Setting up and scaling local or self-hosted LLMs.

• DevSecOps and authoring CI/CD pipelines across Dev, Test and Prod.

• AI-assisted development tooling (GitHub Copilot, Claude Code) used in daily work.

• US healthcare revenue cycle, HL7, or medical billing domain experience.

AUTOMATIC DISQUALIFIERS - apply at CV screening

• Primary career in QA, testing, performance testing, or production support.

• No application code personally merged in the last 12 months.

• Has only ever led QA engineers or testers.

• More than three employers in the last five years, or any role under nine months, unless explained in the submission.