The Architect and Lead Software Engineer will define the target-state architecture for modernized platforms, spanning front-end, API, data, and infrastructure layers. They will lead architectural reviews, mentor engineering teams, and validate designs through prototypes to ensure successful modernization execution.
The Senior Java Engineer will design, develop, and support scalable, high-performance back-end systems using modern cloud-based architectures. They will collaborate with cross-functional teams to deliver high-impact software solutions while utilizing AI-assisted development tools.
The engineer will manage configuration and automation across a large-scale server environment using Chef and Ansible. They will also focus on infrastructure provisioning and the development of CI/CD pipelines to minimize manual operational tasks.
The QA Engineer will be responsible for creating comprehensive test plans and executing manual, automated, and API tests across the software development lifecycle. They will also document and track bugs while collaborating with cross-functional teams to ensure high-quality software delivery.
You will own the data tier, designing denormalized read models and snapshot tables to ensure high-performance patient data access. Additionally, you will manage ETL pipelines, implement data quality checks, and oversee the de-identification path for offshore development.
The Senior Data Engineer will execute data engineering tasks and migrate pipelines from Informatica to Azure Data Factory on a Snowflake-centric stack. They will work within a cross-functional scrum team to take stories from intake through to production.
Design and optimize the data layer for mission-critical applications on Azure and SQL Server, focusing on query performance and concurrency. Partner with application engineers to implement efficient data access patterns and mentor the team on modern data engineering practices.
Design and build full test harnesses for .NET solutions using Playwright and integrate them into Azure DevOps pipelines. Pilot innovative agentic automation and AI-assisted testing patterns to improve coverage and reduce maintenance.
Lead the technical success of complex customer engagements by owning architecture and engineering decisions across AI, data, and service workloads. This hands-on role involves writing production code, mentoring engineers, and translating domain requirements into production-ready designs.
