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Ensemble Health Partners

End-to-end revenue cycle management for hospitals

Senior Engineer - Software

AI Application Engineering +1Updated on Nov 10
Full-timeRemote in USA$120k - $175k

About the Job

Requirements

  • Five or more years of hands-on software engineering experience building and operating production SaaS applications, platforms, or distributed systems.
  • Strong fundamentals in software design, REST APIs, data structures, distributed systems, asynchronous processing, and event-driven architectures.
  • Strong proficiency in Python and experience with one or more additional modern languages such as Java, TypeScript/JavaScript, or C#/.NET.
  • Experience owning production systems end to end, including architecture, implementation, testing, deployment, observability, reliability, and production support.
  • Experience with modern cloud platforms and engineering practices, including Azure or AWS, Docker, Kubernetes or container orchestration, CI/CD, Infrastructure as Code, relational databases, and observability tooling.
  • Experience designing reusable platform capabilities, APIs, SDKs, internal developer tooling, or services consumed by other teams.
  • Experience identifying and solving production performance, reliability, or scale problems.
  • A product mindset and desire to understand users, outcomes, and operational context rather than simply implementing requirements.
  • Strong written and verbal communication skills and ability to explain technical tradeoffs clearly.
  • Experience mentoring or providing technical guidance to other engineers.
  • Must be inquisitive and demonstrate openness to innovation, including AI, to explore better processes and ways to alleviate friction and improve patient and client experiences.

Responsibilities

  • Design, build, deploy, operate, and continuously improve production platform capabilities and Task Agents end to end.
  • Build reusable services, APIs, SDKs, automation components, and platform abstractions rather than solving each workflow as a one-off implementation.
  • Develop Task Agents that work across APIs, browser interfaces, computer-use workflows, data stores, messaging systems, and enterprise applications.
  • Evolve platform capabilities for authoring, deterministic execution, AI-assisted self-healing, testing, orchestration, observability, auditability, and operational control.
  • Apply AI and LLM capabilities where they meaningfully improve Task Agent development, recovery, reasoning, or user experience while maintaining reliable and observable production execution.
  • Design systems that operate reliably at scale, diagnosing bottlenecks and improving performance, availability, cost, and operational efficiency.
  • Own software beyond implementation, including automated testing, CI/CD, monitoring, incident response, debugging, and lifecycle improvement.
  • Work with users and product partners to understand workflow problems, prototype solutions, measure outcomes, and iterate from production feedback.
  • Evaluate open-source technologies, cloud services, AI models, and commercial products and make pragmatic build-versus-buy decisions.
  • Mentor engineers through design discussions, code reviews, debugging, and hands-on technical collaboration.
  • Travel to and work onsite at client, temporary, or corporate office locations as business needs require.

Desired Qualifications

  • Hands-on experience integrating LLMs or AI models into production software, including model APIs, structured outputs, tool use, retrieval, agents, evaluation, or inference infrastructure.
  • Experience with browser automation, computer-use automation, RPA, Playwright, Stagehand, Selenium, UiPath, Power Automate, or similar technologies.
  • Experience building systems where deterministic software and AI capabilities work together to automate complex workflows safely and reliably.
  • Experience with production AI concerns such as evaluation, grounding, model selection, latency, cost management, rate limiting, observability, guardrails, and human-in-the-loop workflows.
  • Experience with FastAPI, PostgreSQL, Redis, Databricks, Azure AI Foundry, Azure OpenAI, AWS Bedrock, SageMaker, or comparable technologies.
  • Experience building systems in healthcare, fintech, or another regulated environment.
  • Familiarity with healthcare integration standards or platforms such as FHIR, HL7, Epic, or payer systems.

About the Company

Ensemble Health Partners

End-to-end revenue cycle management for hospitals

Ensemble Health Partners provides end-to-end revenue cycle management for hospitals and health systems. It handles the entire process from patient intake to final payment, with teams and technology embedded into the provider's operations and a revenue model tied to performance improvements. The company uses its proprietary EIQ platform (analytics, AI, and workflow automation) to optimize revenue cycle processes, reduce insurance denials, and speed cash collection, managing more than $39 billion in net patient revenue. Its approach differentiates it by being a true managed-services partner with full accountability for financial outcomes and a track record of meeting initial client goals. The overarching goal is to improve healthcare providers’ financial performance so they can focus on patient care.

Company size
5,001-10,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Cincinnati, OH
Founded
2014

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