Anomaly

Build scalable APIs, integration logic, and data pipelines to translate complex healthcare data into actionable insights. | Over 5 years professional software engineering experience with proficiency in Python, Java, or Scala and experience with ML pipelines, SQL, and low-latency APIs preferred. | About Anomaly Founded in 2020, Anomaly uses AI and healthcare transaction data to decode complex payer behavior and close the knowledge gap between providers and payers. Our AI engine, Smart Response, analyzes hundreds of millions of healthcare encounters in real time to detect shifting payer rules and denial patterns. By continuously adapting to payer logic, it helps providers predict denials, reverse revenue loss, and hold payers accountable. Our Products and Stack Anomaly builds a suite of machine learning and analytics products designed to uncover health insurance company payment patterns. Our products include: Detect - a web front-end product to surface newly discovered insurance payment patterns and behavior changes utilizing time-series analyses. Predict - high-throughput API for machine-learning-powered claim denial prediction with configuration and monitoring live in the web front-end. Recover - an analytics-driven product to prioritize denied accounts in order to assist our clients in denial recovery using algorithmic ranking and recommended actions that are fine-tuned towards high-dollar denial reversals. Overview As a Senior Fullstack (Backend Leaning) Engineer, you will build the tools that help healthcare providers stand their ground against insurance giants. We’re looking for a Senior Backend Engineer to build the architecture, the APIs, and the integration logic that brings our product to life. You will work on translating complex healthcare data and machine learning outputs into scalable, real-time systems that deliver clear, actionable insights to end users. You will report directly to the CTO. This role is open to fully remote, US-based candidates, with occasional travel to our NYC headquarters. Responsibilities Build integrations with healthcare and financial systems Automate end-to-end data ingestion and delivery pipelines, with a strong focus on observability and data quality Build GenAI features and chat to solve real problems and build user confidence, backed by rigorous evaluation loops and guardrails Design high-throughput, low-latency systems where performance is a mission-critical requirement Be the glue between our PhD-level Data Scientists and Front-end Engineers, taking raw outputs and building the APIs that drive a full, impactful product Qualifications 5+ years of professional software engineering experience Ability to write idiomatic, testable, and maintainable code in Python, Java, or Scala A “hacker mindset” — pragmatic, curious, and solution-oriented Nice to have Experience building reliable data and ML pipelines using SQL, Spark, or Airflow Experience building and deploying online machine learning products Experience developing high-volume, low-latency APIs