Application Engineer, Sap

Google Google · Big Tech · Hyderabad, Telangana, India

This role focuses on designing, building, and deploying Generative AI applications and LLM-based intelligent agents to automate enterprise workflows. The Application Engineer will lead development, testing, and implementation, working with cross-functional teams and serving as a solution architect.

What you'd actually do

  1. design, build, and deploy production-grade Generative Artificial Intelligence (AI) applications and Large Language Model (LLM)-based intelligent agents, embedding autonomous capabilities into enterprise workflows to drive advanced automation.
  2. Write clear, modular, well-structured, and self-sustaining codes, and develop overall systems design, research, and evaluate vendor supplied applications, and develop recommendations on those applications.
  3. Build internal solutions, with custom front-end and back-end services with minimal assistance, and identify processes and solutions to ensure controls compliance can be enforced and monitored.
  4. Help design, build, and deploy internal business applications to support Google’s technology lifecycle, collaboration and spaces, service delivery management, and data and business intelligence.
  5. Conduct and oversee testing of application modules to ensure application meets specifications and collaborate with analysts and business process owners within one or more teams to help translate business requirements into technical solutions.

Skills

Required

  • SAP HANA
  • Advanced Business Application Programming (ABAP)
  • SAP development methodologies (e.g., Fiori, Core Data Services, OO ABAP, OData, REST, enhancements/BADI’s etc.)
  • software development
  • testing

Nice to have

  • Python
  • C
  • C++
  • Java
  • Kotlin
  • JavaScript
  • leading high-level strategic consultations with cross-functional technical teams
  • analyze comprehensive program goals
  • map complex technical dependencies
  • engineer optimal integration solutions across SAP ecosystems and proprietary First-Party (1P) products
  • deliver complex software projects
  • high volume and secure system integrations at scale

What the JD emphasized

  • production-grade Generative Artificial Intelligence (AI) applications
  • Large Language Model (LLM)-based intelligent agents
  • embedding autonomous capabilities into enterprise workflows
  • drive advanced automation
  • cross-functional team of Googlers
  • act like an owner
  • take action and innovate
  • end-to-end ownership
  • coordinating and empowering global, cross-functional teams
  • internal Full Time Employees (FTEs) and external vendors
  • Google Cloud accelerates every organization’s ability to digitally transform its business and industry.
  • enterprise-grade solutions
  • Google’s cutting-edge technology
  • tools that help developers build more sustainably.
  • Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
  • custom front-end and back-end services
  • controls compliance can be enforced and monitored.
  • support Google’s technology lifecycle, collaboration and spaces, service delivery management, and data and business intelligence.
  • application meets specifications
  • translate business requirements into technical solutions.
  • SAP HANA.
  • Advanced Business Application Programming (ABAP)
  • SAP development methodologies (e.g., Fiori, Core Data Services, OO ABAP, OData, REST, enhancements/BADI’s etc.)
  • software development and testing.
  • leading high-level strategic consultations
  • cross-functional technical teams
  • analyze comprehensive program goals
  • map complex technical dependencies
  • engineer optimal integration solutions
  • SAP ecosystems and proprietary First-Party (1P) products.
  • deliver complex software projects
  • high volume and secure system integrations at scale.

Other signals

  • design, build, and deploy production-grade Generative Artificial Intelligence (AI) applications
  • Large Language Model (LLM)-based intelligent agents
  • embedding autonomous capabilities into enterprise workflows