Key skills
JavaPythonScalaLarge-scale distributed systemsDocument processing pipelinesHealthcare claims processingAI/ML production systemsLLM prompt engineeringRetrieval-Augmented Generation (RAG)Workflow automationMonitoring and observability toolsPrometheusGrafanaData structuresAsynchronous programmingSystem designBig-data toolsSparkFlinkKafkaAirflowRayTesting and code quality disciplineCollaborative mindsetAIMLLLMRAGAgenticData Engineering
About this role
Machinify is a leading healthcare intelligence company with expertise across the payment continuum, delivering unmatched value, transparency, and efficiency to health plan clients across the country. As a Staff Software Engineer, you will lead the design and development of large-scale systems that integrate cutting-edge AI into production to enhance Payment Integrity and Audit solutions.
Responsibilities:
- Lead development of document processing pipelines capable of annually handling hundreds of millions of documents, including medical records, claims, and benefits data
- Design and implement agentic workflows that review and validate millions of healthcare claims per year, ensuring accuracy and payment integrity
- Evolve our agentic ecosystem by driving innovation in prompt development lifecycle, optimal utilization of various flavors of multi-modal (text + vision) LLMs, context extraction, RAG, workflow orchestration frameworks, observability and logging, and explainability of LLM outputs
- 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
Requirements:
- 6+ years of software engineering experience, including at least 2 years building agentic systems or AI-driven workflows in an enterprise setting
- 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
- 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)
- 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
- Experience with big-data tools and distributed systems frameworks (e.g., Spark, Flink, Kafka, Airflow, Ray) is a strong plus