Machinify is looking to transform Payment Integrity and Audit solutions by bringing cutting-edge AI into production, automating complex workflows, and maximizing financial outcomes while driving down healthcare costs.
Requirements
- Strong programming expertise in Java and Python, with additional experience in Scala a significant plus.
- Experience designing and scaling large-scale, distributed systems and pipelines, ideally processing unstructured data such as documents or healthcare records.
- Proven ability to productionize AI/ML techniques (e.g., LLM prompt engineering, RAG, workflow automation, and agents) with a focus on reliability, observability, and explainability.
- Knowledge of monitoring and observability tools (Prometheus, Grafana or similar) and passion for tracking metrics.
- Strong CS fundamentals, including data structures, asynchronous programming, and system design.
- Track record of building and shipping enterprise-grade AI/ML systems in production.
- Strong testing and code quality discipline, with experience contributing to and improving enterprise-grade systems.
Responsibilities
- Lead development of document processing pipelines capable of annually handling hundreds of millions of documents, including medical records, claims, and benefits data.
- Collaborate across teams (Data Science, Data Engineering, and Product) to deliver robust, end-to-end AI-powered systems that automate complex workflows.
- Address critical infrastructure needs by tracking and reducing tech debt while strengthening system reliability and scalability.
- Mentor and guide engineers on best practices in designing production-grade AI systems, helping set technical direction for the team.
Other
- 6+ years of software engineering experience
- Demonstrated success in reducing manual processes through automation, ideally in healthcare, fintech, or other regulated domains.
- Collaborative mindset with experience working closely with data scientists and cross-functional teams to translate requirements into technical designs and production systems.
- A passion for pushing the boundaries of AI to deliver better-than-human-level accuracy and efficiency at scale.
- Bachelor’s or Master’s degree in Computer Science or a related field (or equivalent practical experience).
