Nuna is a health-technology startup headquartered in San Francisco, California. We partner with organizations to make a positive impact through data-driven healthcare projects.

Nuna is the Korean word for big sister. Founder and CEO Jini Kim is ‘nuna’ to her brother Kimong, who was diagnosed with severe autism at two years old and grand mal epilepsy at eight. Faced with the possibility of debilitating medical debt, at age 9 Jini helped her immigrant parents navigate the convoluted American healthcare system and managed to register Kimong for Medicaid.

Repairing American healthcare became Jini’s life work. Nuna was founded on the belief that connecting healthcare payers, providers, and patients with insights derived from data is a critical foundation for healing this ailing system.

In 2013, Jini was enlisted by the White House to save the embattled rollout of In 2014, Nuna began work on the first standardized data platform for Medicaid, which stores the data of over 73 million poor, disabled, and children across the United States. Over this time, Nuna also began working with large, self-insured employers and health plans to improve quality of care for their populations. In two rounds of funding with Kleiner Perkins Caufield Byers, John Doerr, and others, Nuna has raised over $90 million dollars.

Today, Nuna has grown to over 120 engineers, data scientists, designers, and experts in economics, health policy, privacy, security, and corporate operations. We are united in our dedication to a brighter future for American healthcare.

At Nuna Engineering, we build so that everyone can use, learn, and act. Our technology enables data scientists, analysts, benefits officers, and policymakers to understand healthcare data while ensuring its integrity, security, and privacy. Our work runs the gamut, from joining multiple streams of messy real-world data to building queryable data warehouses to constructing visualizations and dashboards that provide actionable insight. We build systems that are auditable, as automated as possible, accurately represent the underlying data, and, perhaps most importantly, responsive to our end users' needs. We strive for a creative, collaborative engineering environment that implements best practices for peer review, readability, maintainability, and security of the code base and infrastructure.

Government Services:

The Government Services team is responsible for expanding upon our existing work with federally funded healthcare programs (like Medicare, Medicaid, Veteran’s Administration, etc). This work is crucial to our mission of making healthcare more accessible and valuable to all people. The team works with detailed data at a massive scale to enable analysis and insights to be derived from processing.


The commercial team is responsible for expanding upon our existing work with commercial self-insured entities. These entities (large employers etc) need to understand how the benefits they are providing to their constituents are actually being used, whether those people are getting quality care or not, and whether programs put into place are having the desired effect. The team works with data from many different sources, processes it, and provides tools for our data scientists.

Network Products:

The Network Products team is responsible for creating products that help payers (e.g., health networks) select, incentivize and pay for providers and match these providers to patients in ways that ultimately make high-quality healthcare affordable. The team helps to ingest data from different sources, perform machine-intensive computations and transformations on it, and deliver the results back to payers in order to achieve these goals.

Skills and responsibilities

  • Provide architectural guidance and oversight to projects within a team.
  • Be a mentor to junior and mid-level engineers.
  • Enforce high quality coding standards and practices via reviews and by demonstrating this in their own work.
  • Have a bias to action.
  • Be able to help others break down large team goals into specific and manageable tasks.
  • Be involved and supportive of agile sprint model of development,  helping to enforce the practice and the discipline.
  • Able to work efficiently and proactively across engineering teams to enable us to deliver on our goals of loosely coupled, adaptable, scalable solutions.
  • Have a good understanding of where their project fits into the larger goals for engineering and adapts their work so that the priorities of the systems they are creating match those of the organization.


  • Location:
    San Francisco
  • Salary: , We provide a balance of cash and equity, as we're a Series B company.
  • Deadline:


Minimum qualifications

  • Excellent communication skills
  • Ability to deal well with ambiguity and act with autonomy
  • 5+ years of experience in this or a related field
  • Technology-agnostic and pragmatic engineering sensibility, focused on solving key problems, not the tools
  • Knowledge of computer science fundamentals (such as debugging or object oriented design) and software engineering processes (such as agile software development)
  • Demonstrated ability to understand automated testing concepts and ability to consistently apply those concepts
  • Working experience with distributed computing infrastructure (Hadoop, Spark, Crunch, etc)
  • Knowledge of database fundamentals for large scale, analysis-heavy databases
  • [Bonus] Experience designing and building loosely coupled, adaptable, scalable systems
  • [Bonus] Familiarity with Django web applications or similar web frameworks
  • [Bonus] Experience building tools for data analysis or data analysis platforms
  • [Bonus] Experience building mobile web application backends

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