• Design, develop, and maintain Java-based backend applications and services. • Implement and maintain authentication and identity integrations (Okta, LDAP). • Develop APIs and backend services supporting enterprise web applications. • Work with event-driven and messaging architecture. • Integrate with Azure cloud services. • Maintain secure access to services using Key Vault / secrets management. • Collaborate with frontend teams (JavaScript-based applications). • Support enhancements, bug fixes, and ongoing maintenance of existing systems. • Ensure performance, scalability, and security of backend services.

• Represent Mondelēz International by visiting stores according to the agreed planning cycle • Monitor shelf placement and assortment • Set up campaign displays and secure prime in-store locations • Perform necessary administrative tasks • Optimize the use of our point-of-sale (POS) materials • Be the customer's preferred supplier • Create product displays in stores

• Define and evolve the enterprise identity security architecture and identity trust model • Design identity architectures supporting workforce, external, privileged, and machine identities across hybrid and cloud environments • Establish identity trust boundaries, authentication flows, and authorization models across enterprise systems • Define enterprise identity policy enforcement models supporting Zero Trust access architectures • Design identity federation architectures using SAML, OAuth2, OpenID Connect, and token-based identity frameworks • Define identity trust relationships across enterprise identity providers, SaaS platforms, partner ecosystems, and external identity providers • Establish identity session management, token security, and authentication lifecycle standards • Define enterprise access control models including RBAC, ABAC, and policy-based authorization • Design identity policy enforcement patterns using centralized policy engines and identity-aware access controls • Define access policies supporting risk-based authentication and contextual access controls • Design security architecture for non-human identities including service accounts, application identities, API credentials, and workload identities • Define identity models supporting microservices, containers, APIs, and cloud-native workloads • Reduce enterprise identity attack surface through automated identity lifecycle and least-privilege access controls • Design identity architectures supporting multi-cloud environments, SaaS ecosystems, and modern application platforms • Define architecture supporting B2B partner access and B2C external identity models • Enable identity-driven access control across enterprise applications, APIs, and digital services • Define architecture supporting identity threat detection and identity risk monitoring • Integrate identity platforms with security operations monitoring and threat detection frameworks • Design controls to detect and mitigate credential compromise, privilege escalation, and anomalous authentication activity • Establish identity telemetry patterns enabling identity-based security analytics • Define enterprise identity architecture standards, design principles, and technical reference patterns • Lead architecture governance for IAM integrations across enterprise applications, cloud platforms, and infrastructure services • Conduct architectural reviews of identity integrations and authentication models for new systems • Provide technical guidance to engineering teams implementing IAM services and integrations

• Design and evolve our external API and embedded product layer, ensuring long-term stability, disciplined versioning, and enterprise-grade API craftsmanship. • Evolve our agentic retrieval harness to support both patient and clinical search workflows across structured and unstructured data, with strict permission and audit guarantees. • Build reusable platform primitives that allow external partners to embed and extend our AI capabilities — ensuring every integration produces lasting platform leverage. • Contribute to our core data models that unify structured health records, unstructured inputs, and high-frequency time-series signals.