Integrate machine learning models into production SaaS features by deploying model-serving endpoints, building Python or Node.js microservices, designing REST APIs, and supporting React interfaces. Optimize inference performance, scalability, and reliability through caching, asynchronous processing, and batching. Containerize and orchestrate services, maintain API contracts, implement CI/CD and automated tests, and collaborate with data science, product, QA, and engineering teams.

Designs, configures, tests, documents, and supports customer integrations throughout SaaS implementation lifecycles. The role uses APIs, webhooks, SFTP, EDI, data transformations, and middleware while troubleshooting connectivity and validation issues. It leads technical discovery, creates integration flows and test plans, collaborates with customers and internal teams, supports post-launch issues, and improves implementation processes through reusable templates, automation, and documentation.