Senior Software Engineer

We are looking for a Senior Software Engineer who has helped build and scale software during a period of rapid company growth.

The ideal candidate has worked at an early-stage or high-growth startup and has personally taken products or services from 0 to production to meaningful scale. You should be comfortable owning a system end-to-end: understanding the problem, designing the architecture, building the application, deploying it, operating the infrastructure, and improving it as usage grows.

This is not a role where requirements are handed down and engineering simply implements them. We want someone with strong technical intuition who can look at an ambiguous problem, determine what should be built, identify the right abstractions, and ship quickly.

You will work heavily on the infrastructure and AI pipelines behind CuraFi’s products, including distributed processing systems, healthcare integrations, AI agents, document intelligence, APIs, and production LLM applications.

In this role, you will:

• Own critical products and services end-to-end across architecture, development, deployment, infrastructure, monitoring, and scaling.
• Design and operate distributed systems and asynchronous processing pipelines handling large volumes of healthcare data and workflows.
• Build production AI systems using LLMs, agents, retrieval systems, document intelligence, and custom AI pipelines.
• Develop infrastructure for LLM-powered applications including evaluation, prompting, tool use, guardrails, observability, and reliability.
• Build document processing and LLM/OCR pipelines capable of transforming complex healthcare documents into structured, actionable data.
• Design high-performance APIs and integrations with healthcare systems, external vendors, and third-party platforms.
• Build systems that remain reliable as workloads increase by orders of magnitude.
• Make pragmatic architecture decisions that balance speed of development with long-term scalability.
• Experiment aggressively with new AI models, frameworks, coding tools, and infrastructure-and develop strong opinions about what works in production versus what does not.
• Debug difficult issues across application code, distributed workers, databases, infrastructure, networking, and third-party systems.
• Work directly with product, operations, customers, and other engineers to turn real-world workflow problems into scalable software.
• Help establish the technical patterns, infrastructure, and engineering culture that CuraFi will build on as the company grows.

• 5+ years of software engineering experience is ideal, with significant experience building production systems.
• Strong startup experience, particularly at an early-stage or rapidly scaling technology company.
• Experience helping a product or platform move from 0 * 1 and then from 1 * scale.
• A track record of owning production services end-to-end, including architecture, implementation, deployment, infrastructure, monitoring, and ongoing operation.
• Strong Python experience and a deep understanding of backend engineering.
• Strong knowledge of distributed systems, asynchronous processing, queues, workers, concurrency, failure handling, and system reliability.
• Experience designing and operating systems on AWS.
• Experience building production APIs and complex third-party integrations.
• Experience building AI-powered applications using modern LLMs.
• Familiarity with agent frameworks such as LangChain or LangGraph, or experience building comparable orchestration systems directly.
• Experience with retrieval systems, embeddings, vector databases, or platforms such as Pinecone.
• Experience building document intelligence, OCR, multimodal, or LLM-based extraction pipelines is highly valuable.
• Practical understanding of prompt engineering, structured outputs, evaluations, guardrails, context management, and production LLM reliability.
• Experience with voice AI agents or real-time AI systems is a plus.
• Strong SQL and relational database fundamentals.
• Strong intuition around system architecture and an ability to recognize when something should be simple versus when additional infrastructure is justified.
• Comfort working in an environment where requirements may be incomplete, priorities can change quickly, and engineers are expected to exercise judgment rather than wait for detailed specifications.
• High curiosity around new developer and AI tooling. We want engineers who actively experiment with the latest coding agents, models, frameworks, and infrastructure and understand how to use them to dramatically increase engineering velocity.

Most importantly, we are looking for someone who has actually built and scaled systems in a startup environment, experienced the technical problems that emerge as a product grows, and helped establish the engineering foundation needed for the next stage of the company.

CuraFi builds software and AI systems that help healthcare organizations automate complex administrative and clinical workflows.

Healthcare infrastructure is fragmented, operationally intensive, and filled with problems that require combining software engineering, AI, domain knowledge, and systems thinking. We believe many of these workflows can be fundamentally redesigned using modern AI.

We are building the technical foundation to make that possible.

CuraFi is an equal opportunity employer. We value people with different backgrounds, experiences, and perspectives and are committed to building an environment where exceptional people can do their best work.

Pay: $180,000.00 - $210,000.00 per year, * 401(k)

• 401(k) matching
• Dental insurance
• Health insurance
• Life insurance
• Paid time off
• Vision insurance

CuraFi is building AI-native infrastructure for healthcare operations. We work on complex, high-impact problems across clinical workflows, healthcare data, automation, and decision support-using AI to turn traditionally manual, fragmented processes into scalable software systems.

Our engineering team operates like an early-stage startup team: small, highly technical, and deeply involved in the product. Engineers work across application development, AI systems, integrations, infrastructure, and deployment rather than being limited to a narrow part of the stack.

We care about moving quickly without creating fragile systems. The problems we solve often begin loosely defined, involve messy real-world data and workflows, and ultimately need to operate reliably at significant scale.