What we do

We’re fixing one of the most broken and costly pieces of the US healthcare system: medical billing.

Today, healthcare providers spend over $250B each year on administrative overhead just to get paid by insurance. Medical billing is expensive because it’s nuanced and hard - maybe ~100x harder than credit card payment processing - and because it’s traditionally done by armies of humans who track and manage complex rules and processes specific to individual insurance companies with little or no supporting software.

We’re rethinking medical billing from the ground up, using data science and machine learning to automate much of this complexity, so healthcare providers can get paid dramatically more easily and inexpensively.

Since finishing the Y Combinator W20 batch we've been funded by an incredible group of funds + angel investors. We have many more customers begging to use our product than we have bandwidth to serve, which is why we need you to help us scale!

About Candid

At Candid Health, we're on a mission to revolutionize healthcare by solving one of its most complex and costly problems: the billing and revenue cycle management (RCM) process. The healthcare system has long been burdened by slow, inefficient workflows that waste valuable resources, leaving providers with less time and money to focus on patient care. With our cutting-edge revenue cycle automation platform, we are transforming this space through an intelligent, data-driven approach that simplifies billing, enhances claims processing, and eliminates administrative waste.

The Role

As an AI Engineer at Candid health, you’ll be empowered to bring Artificial Intelligence & Machine Learning to the forefront of healthcare automation. This is an opportunity to get in at the ground floor of designing and building something exciting and new - generating immense value to both medical providers and their patients. You will be responsible for translating compelling initial prototypes into a foundational set of differentiated, high impact ML/AI use cases throughout our platform and across our customer base.

We’re looking for a tastemaker and strong hands-on builder who can effectively navigate the complexities of our problem space – medical billing– and leverage their technical expertise to deliver strategic AI- & ML-based solutions leading to impactful business outcomes.

What You’ll Do

• Expansively Own Outcomes & Apply AI to Real Problems: Candid’s mission is to use technology to rebuild the backbone of American healthcare. The innovations we make have the potential to change both medical providers and patient experience in a meaningful way. You are responsible for Candid delivering on outcomes for both internal teams and external customers through, but not limited to, building AI features into Candid’s platform.
• Innovate and Drive our Technical AI Strategy: Identify and drive opportunities on when, where and which AI/ML techniques can deliver business value. Research industry best practices, leverage state-of-the-art technologies and tools to design systems and support the necessary outcomes in a forward looking and responsible manner. Take compelling initial prototypes we’ve built and ensure we have a strong foundation to scale and deploy them across our customer base.
• Scale and Unlock New & Existing Products: Partner with leadership and cross-functional teams to automate and scale products and workflows with the most technical complexity, such as claim submission, resubmission, and workflow optimization. You will drive Candid’s AI roadmap and directly influence our product roadmap across the board to enable Candid’s customers to optimize their RCM operations at scale.
• Build AI Infrastructure: Architect the infrastructure that will allow us to leverage AI across every facet of our product. Structure and format our data to better support AI development. Establish rigorous processes for model training, testing, and monitoring—ensuring they are scalable, extensible, and meet our high expectations for security standards.

Who You Are

• Bachelors or Masters of Science in Computer Science, Computer Engineering, Math or other similar degree.
• 8+ years of experience building software of significant scale and complexity.
• 5+ years of AI engineering experience in a professional setting, preferably applying it to real world solutions.
• You’ve built systems that leverage ML technologies (e.g. built or used specific NLP models), and know what tools, frameworks, and libraries to use.
• You understand the pros, cons, and tradeoffs of leveraging various AI solutions across a wide variety of use cases, and can help us make informed decisions around when to use deterministic (ML) vs. non-deterministic (LLM) approaches to deliver the best ROI, efficiency improvements, & cost savings.
• you know the right architecture and patterns to build something of enduring value and scale.
• You have a customer-first and learner’s mindset, and value teaching others.
• You make the right trade-offs when considering project scope, which corners are worth cutting, and which are not.
• You’re a clear and concise communicator; you enjoy the challenge of explaining complicated ideas in simple terms, both in-person and in writing.
• Experience with the technologies we currently use is a plus, but by no means required: Google Cloud Platform, BigQuery, PostgreSQL, Metabase, Terraform, Python.

Back: modern Python (async, type annotated) ~mini services, Celery + Redis for task queues, Postgres.

Front: Typescript + React. Good use of hooks + styled components.

Infra: Containerize all the things. docker-compose locally, Kuberntes + Istio on GCP. Pretty sophisticated developer tooling + CI (Github Actions) given our size.