About us
Klearforce is building an AI native platform that helps manage insurance eligibility, claims, ERA/payments, and revenue workflows. Our goal is simple: eliminate administrative burden so offices can focus on patient care. We’re a small, fast-moving team building AI-powered products that are already creating measurable impact for customers.
Role
We’re looking for a Full-Stack Software / AI Engineer with 4–6 years of experience building production systems. You’ll work directly with company leadership to design, build, and ship features across our platform. This is a high-ownership role where you’ll contribute across the entire stack—from customer-facing workflows to backend services, integrations, and AI agents.If you enjoy solving messy real-world problems, building AI-powered products, and owning systems end-to-end, we’d love to talk.
You’ll do
- Design and ship full-stack features from idea to production
- Build AI-powered workflows using agentic patterns and human-in-the-loop review
- Integrate with third-party systems, APIs, webhooks, EDI feeds, and browser automation tools
- Develop reliable backend services and customer-facing experiences
- Improve prompt engineering, structured outputs, tool-calling workflows, and agent orchestration
- Build systems that handle failures gracefully and provide clear user feedback
- Write tests, participate in code reviews, and continuously improve code quality
- Collaborate closely with customers to understand operational workflows and automate them
Required Experience
- 4–5 years of professional software engineering experience
- Strong TypeScript experience across frontend and backend systems
- Experience building production applications with React/Next.js
- Experience building APIs with Node.js, NestJS, or similar frameworks
- Hands-on AWS experience (DynamoDB, S3, ECS, Lambda, or similar)
- Experience integrating external systems and APIs
- Experience deploying and operating production software
- Strong understanding of debugging, observability, testing, and reliability
AI Experience
You don’t need to be a machine learning researcher, but you should have experience building with modern LLMs in production:
- Prompt engineering and structured outputs
- Tool calling and agent workflows
- Evaluating and improving AI-generated responses
- Handling model failures, retries, and human review flows
- Experience with Bedrock, OpenAI, Anthropic, or similar platforms
Nice to Have
- Experience building agentic AI systems
- Bedrock AgentCore or Strands experience
- Python for experimentation and evaluation tooling
- Understanding of ML fundamentals and evaluation methodologies
- Experience with healthcare, insurance, revenue cycle management, or EDI workflows