Role summary: Develop, enhance, and operate a production-grade AI platform that automates procurement compliance checks across the procure-to-pay lifecycle. The role focuses on platform engineering, enterprise integrations, AI pipeline operationalization, observability, and cloud-native solution delivery, ensuring AI capabilities are scalable, reliable, and auditable. Key responsibilities: - Design, build, and maintain cloud-native services and data integration pipelines supporting AI-powered compliance workflows - Develop and enhance document processing and orchestration pipelines using Azure Functions and event-driven architectures - Integrate enterprise systems including SAP, Snowflake, Cosmos DB, and other source-of-truth platforms - Build and operate evaluation infrastructure, telemetry, monitoring dashboards, and operational tooling for AI services - Implement CI/CD, automated testing, and production support practices to ensure platform reliability and security - Collaborate with Data Scientists and product teams to productionize AI capabilities and continuously improve platform performance ### Requirements Mandatory skills: - Strong Python development experience with production-grade, testable, and maintainable code - Experience building and operating applications on Azure cloud, including serverless and event-driven architectures - Strong knowledge of data integration, SQL, and enterprise data platforms such as Snowflake or similar warehouses - Experience developing APIs, microservices, and distributed systems - Hands-on experience with CI/CD pipelines, Git-based development, and DevOps practices - Strong understanding of observability, including logging, tracing, performance monitoring, and operational dashboards Preferred skills: - Experience with Azure OpenAI, Azure Document Intelligence, OCR, or AI-powered applications - Familiarity with LLM integration, prompt orchestration, and AI application development - Experience integrating with SAP, OData services, or enterprise ERP platforms - Experience working in agentic development environments and AI-assisted engineering workflows Experience: - 5–10+ years of experience in software engineering, cloud application development, or platform engineering - Proven track record delivering and supporting cloud-native, enterprise-scale applications in production environments - Experience working in AI, data-driven, or intelligent automation platforms is highly desirable