Why RapidClaims

US healthcare providers are paid only after every visit is turned into billing codes and submitted as a claim. That work is manual, slow and error-prone, and it is getting harder: claim denial rates have nearly doubled in a decade, from 7% to over 13%, while provider margins have fallen from around 10% to just 1% to 2%. Fixing the revenue cycle is now one of the biggest priorities for every health system in the country, and AI is how they are trying to fix it.

RapidClaims is an AI revenue cycle platform. Our autonomous agents code medical records, improve clinical documentation and manage denials, across 25+ specialties, with 98%+ coding accuracy. Clients include Federally Qualified Health Centers (FQHCs), specialty physician groups, community health centers and hospital systems. The company has raised $11 million in total funding from top investors, including Accel and Together Fund.

What sets us apart is speed to value. Where incumbents need tens of thousands of records and months of implementation to cover a current specialty, we need a few hundred records and hours. That advantage only counts if every client goes live quickly, stays stable and keeps growing. This role exists to make sure they do.

Why this role exists

In AI for the revenue cycle, the model is no longer the hard part. The hard part is making it work inside a real provider's workflow: their electronic health record (EHR) system, their specialties, their payer mix, their coders and their habits. The companies winning this market are the ones that get clients live fastest and keep them stable at scale. For a client, the deployment is the product.

Every client goes through the same journey with us: a pilot to prove value, a go-live, a period of stabilisation, then expansion into more of their work. Each stage depends on several teams pulling in the same direction, and we are hiring so that one owner holds that together.

The team you will join is responsible for pilots and live clients. You will work with engineering, data science, operations and quality control every day. You will wear multiple hats: problem solving, design thinking, debugging client issues and getting them resolved, and working with operations to manage client volume and bring efficiency.

What you will own

● The deployment. Run pilots, take clients live, stabilise them and lead their expansion. You are accountable for the client's outcome end to end, and you are the

person who knows where every client stands today.

● The translation.



Convert client needs into clear, prioritised asks for our teams, and convert our progress into updates the client can act on. Nothing gets lost between the client and the people building for them.

● The resolution. Trace an issue across data, workflow, model and people, route it to the right owner, and drive it to closure. You report problems solved, not problems found.

● The tooling. Prototype agents, prompts and automations that remove manual steps from this job, deploy them, and measure the impact. Where a process is repeated, you are expected to build rather than repeat.

● The product. Turn patterns you see across clients into product features and process changes, so that every client after yours runs on what you learned.

Your first 45 days

● By day 15. You understand how a chart moves through our platform and through a client's revenue cycle. You have shadowed a live account, sat in on client calls, and mapped where work gets stuck and why.

● By day 30. You are running a pilot: discovery, data and integration scoping, workflow setup with data science, and the first quality review with the coding and quality control teams. You have shipped one small tool that saves someone on the team hours every week.

● By day 45. You own a portfolio of clients. One automation you built is in daily use by the team, and one product or process change exists because you saw a pattern across clients and made the case.

How we will measure success

● Time from pilot start to go-live, and from go-live to a stable, predictable weekly volume.

● Volume moving on time for your clients, and how quickly stuck work gets unstuck.

● Accuracy and quality outcomes for your clients, and how quickly issues reach data science when the model is the cause.

● Expansion: more of each client's specialties, sites and workflows moving onto the platform.

● Manual effort removed from the team by what you built.

What you bring

● 2+ years of experience, with shipped AI work. At least one AI-driven solution you built and put in front of real users: an agent, an automation,



an internal tool or a product feature. You are hands-on with prompting, agents and evals, and you can

walk us through what you built, how you tested it, and what broke.

● A fast learner. Healthcare billing and medical coding are deep domains. You do not need to know them today, but you need to pick them up quickly and enjoy doing so. We are betting on learning speed over prior domain exposure.

● A structured thinker. You break messy problems down MECE (mutually exclusive, collectively exhaustive), so nothing is missed and nothing is counted twice, and you can hold that structure while the details keep changing.

● Comfort with data. SQL, Python or advanced spreadsheets, enough to answer your own questions without waiting on someone else.

● Clear communication, written and spoken. You will talk to clients, engineers, coders and founders in the same day, and each of them needs a different version of the same truth.

● Comfort with context switching. This role moves between a client call, a stuck batch and a prompt that is not working. It is not a role with long quiet blocks, and the people who thrive in it find that energising rather than draining.

● High ownership and a problem-solving nature. You start with "how do I fix this", and you want the zero-to-one journey with the mess that comes with it.

Good to have. Exposure to healthcare, billing or US insurance. A prior client-facing or operations role at a startup. Familiarity with agent frameworks, structured outputs and tool calling, or LLM evaluation tools.

What this role is not

● Not an implementation or project-management role where you run a checklist and hand off. You build, debug and own the outcome.

● Not a pure operations role. If building your own tools does not excite you, this will feel like the wrong job.

● Not a quiet role. Several clients, several teams, many open threads at once.

Benefits:

- Paid time off
- Provident Fund

Application Question(s):

- Are you willing to work in Koramangala Bangalore office
- How many years of experience in AI
- How many years of experience in AI deployment
- Have you worked in Health care Industry
- How many No. of end-to-end deployment you have completed
- what is your team leading size
- Do you have managerial experience
- What is your current CTC
- What is your expected CTC
- What is your notice period
- Have you been interviewed by Rapid Claims before?

Work Location: In person

📌 AI Deployment Manager (Bengaluru)
🏢 Rapid Claims
📍 Bengaluru