Brandon Bussel

I’m a Senior Software Engineer with 10+ years of experience building AI/ML-powered and data-driven software solutions across healthcare, financial, CRM, business intelligence, and SaaS platforms. I bring deep expertise in Python, C#, and cloud-native architectures, with a focus on improving performance, automating workflows, and deploying Generative AI in enterprise systems. I’m comfortable owning systems end-to-end, from architecture decisions to production deployment, especially in fast-moving Agile environments.

At Molina Healthcare (Nov 2022–Present), I led backend development of a HIPAA-compliant telemedicine healthcare platform by integrating Python-based AI automation and EHR data analytics to improve care coordination across Medicaid and Medicare populations. I optimized microservices and REST APIs—cutting average load times by 45% and improving response time from 800ms to 450ms—by profiling bottlenecks and refactoring data access layers. I architected real-time data synchronization using Kafka for event-driven workflows while maintaining full HIPAA compliance.

I also built a production GenAI support chatbot using LangChain, OpenAI APIs, and a pgvector knowledge base, incorporating RAG pipelines and conversation memory. This reduced average customer resolution time by 50%. I’ve helped deploy and monitor containerized services using Docker and Kubernetes on AWS, and I work with Agile tooling and version control using Jira integrated with Bitbucket.

Before Molina, I contributed core feature development to Salesforce Einstein (Aug 2019–Oct 2022), building Python-based ML pipelines for predictive lead scoring, opportunity ranking, and automated workflow recommendations. I designed and owned high-throughput microservices and data pipelines processing millions of CRM records daily, and I shipped secure, high-performance REST APIs that reduced integration errors for partner teams by roughly 30%. Earlier, at Tableau (Aug 2014–Aug 2019), I developed Python backend scripts and TabPy workflows, improved PostgreSQL performance with query tuning and indexing, and implemented Redis caching to reduce dashboard load times under heavy concurrency.