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 workflowsDevelop and enhance document processing and orchestration pipelines using Azure Functions and event-driven architecturesIntegrate enterprise systems including SAP, Snowflake, Cosmos DB, and other source-of-truth platformsBuild and operate evaluation infrastructure, telemetry, monitoring dashboards, and operational tooling for AI servicesImplement CI/CD, automated testing, and production support practices to ensure platform reliability and securityCollaborate with Data Scientists and product teams to productionize AI capabilities and continuously improve platform performance Mandatory skills: Strong Python development experience with production-grade, testable, and maintainable codeExperience building and operating applications on Azure cloud, including serverless and event-driven architecturesStrong knowledge of data integration, SQL, and enterprise data platforms such as Snowflake or similar warehousesExperience developing APIs, microservices, and distributed systemsHands-on experience with CI/CD pipelines, Git-based development, and DevOps practicesStrong understanding of observability, including logging, tracing, performance monitoring, and operational dashboards Preferred skills: Experience with Azure OpenAI, Azure Document Intelligence, OCR, or AI-powered applicationsFamiliarity with LLM integration, prompt orchestration, and AI application developmentExperience integrating with SAP, OData services, or enterprise ERP platformsExperience working in agentic development environments and AI-assisted engineering workflows Experience: 5–10 years of experience in software engineering, cloud application development, or platform engineeringProven track record delivering and supporting cloud-native, enterprise-scale applications in production environmentsExperience working in AI, data-driven, or intelligent automation platforms is highly desirable
