About The Role

The Mount Sinai West Cardiology AI Research Lab is seeking an experienced and highly motivated AI Applications Engineer II to support the rapid development, implementation, and optimization of AI-enabled clinical applications within a healthcare environment.

This role sits at the intersection of software engineering, clinical workflow improvement, data integration, and applied artificial intelligence. The engineer will work closely with physicians, clinical operations teams, data stakeholders, and technology partners to build practical tools that improve care delivery, streamline workflows, and support innovation within cardiology.

The ideal candidate has strong software engineering fundamentals, experience building full-stack or platform applications, and the ability to move quickly from concept to working prototype. This role is well suited for an engineer who is comfortable working in a fast-moving clinical environment and translating real-world workflow needs into usable, scalable software solutions.

Design, develop, test, and maintain clinician-facing applications, internal tools, dashboards, and workflow-support systems for the Cardiology AI Lab.
Rapidly prototype and iterate on AI-enabled clinical workflows, including tools that support documentation, triage, care coordination, remote monitoring, quality improvement, research operations, or clinical decision support.
Collaborate directly with physicians, advanced practice providers, nurses, administrative leaders, and operational stakeholders to understand clinical workflows and translate user needs into technical requirements.
Build and maintain full-stack applications, APIs, data pipelines, and integrations that support clinical and operational use cases.
Assist with integration of applications into healthcare data systems, institutional infrastructure, and approved technology environments.
Work with clinical and data teams to ensure applications are reliable, usable, secure, and aligned with institutional standards.
Help define implementation processes, user workflows, documentation, and operational protocols for deployed applications.
Support architecture, scalability, maintainability, and production-readiness decisions as applications mature from prototype to operational tools.
Evaluate and apply modern AI-assisted development workflows, large language model tools, automation frameworks, and emerging software development approaches where appropriate.
Participate in testing, troubleshooting, user feedback cycles, and continuous improvement of deployed applications.
Maintain clear technical documentation, workflow documentation, and communication with cross-functional stakeholders.
Ensure that all work is performed in accordance with Mount Sinai policies, privacy standards, data security requirements, and applicable healthcare regulations.

Required

Bachelor’s degree in computer science, Software Engineering, Data Science, Biomedical Informatics, Engineering, or a related technical field.
Minimum of 3 years of professional experience in software engineering, application development, data engineering, AI/ML engineering, clinical informatics engineering, or a related technical role.
Strong programming skills in one or more commonly used languages such as Python, JavaScript/TypeScript, Java, C#, or similar.
Experience building software applications, internal tools, dashboards, APIs, or platform components.
Familiarity with databases, data models, SQL, APIs, and software development best practices.
Ability to work collaboratively with non-technical stakeholders and translate operational or clinical needs into technical solutions.
Strong problem-solving skills and comfort working in ambiguous, evolving project environments.
Excellent communication, documentation, and organizational skills.

Preferred

Experience working in a healthcare, hospital, academic medical center, clinical research, or health technology environment.
Familiarity with EHR data, clinical workflows, healthcare operations, HL7/FHIR concepts, Epic-related workflows, REDCap, OMOP, or institutional data warehouses.
Experience with AI-enabled applications, machine learning workflows, large language models, natural language processing, or AI-assisted software development tools.
Experience developing full-stack applications using modern web frameworks.
Experience with cloud services, containerization, CI/CD pipelines, secure deployment practices, or production software environments.
Familiarity with clinical quality improvement, care coordination, remote patient monitoring, cardiovascular medicine, or cardiology workflows and interest in applied AI, rapid prototyping, and building practical tools that can be used by clinicians and operational teams.