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Accenture

Advises businesses and runs their technology

Custom Software Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeHyderabad, Telangana, IndiaNo salary listedIn-person

About the Job

Requirements

  • At least 3 years of experience is required.
  • Requires 15 years of full-time education.
  • Strong hands-on expertise with SAP BTP Integration Suite concepts and building blocks, including cloud integration, integration flows, transformation patterns, and monitoring.
  • Ability to implement message mappings, routing patterns, and transformation logic across enterprise data formats.
  • Practical scripting capability, such as Groovy, for advanced integration flow customization and performance tuning.
  • Solid API design and management fundamentals, including security, throttling, lifecycle and versioning, and observability.
  • AI-native delivery capability, including tool-augmented workflows, retrieval-grounded outputs, measurable evaluation loops, and safe action boundaries.

Responsibilities

  • Develop custom software solutions by designing, coding, and enhancing components across systems or applications; use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to business needs.
  • Design, develop, and run end-to-end integration scenarios using cloud integration capabilities to connect SAP and non-SAP systems reliably.
  • Build, structure, and manage large integration flows with modularity, reusability, and maintainability for enterprise scale.
  • Create and maintain integration flows using routing, splitting, gathering, and other transformation patterns.
  • Implement message mappings and data transformations for JSON, XML, CSV, and other common enterprise formats, ensuring semantic correctness and downstream compatibility.
  • Apply canonical modeling and contract-first practices to reduce brittle point-to-point dependencies.
  • Use scripting such as Groovy for complex transformation logic, enrichment, validation, and conditional execution paths.
  • Implement message persistence patterns such as data stores to support idempotency, retries, correlation, and resilience.
  • Design and expose secure APIs using API management capabilities, including policies, authentication and authorization, throttling, and versioning.
  • Integrate with third-party applications using connector-based approaches and standardized integration patterns.
  • Enable event-driven integration using messaging and event capabilities for near-real-time propagation and decoupled architectures.
  • Build integration agents that generate initial integration flows from system and endpoint selections and naming conventions, then validate them against enterprise standards.
  • Implement retrieval-grounded assistance using interface catalogs, mapping specifications, standards, runbooks, and known incident patterns to provide verifiable recommendations.
  • Apply intelligent mapping and configuration recommendations to accelerate build work and reduce rework.
  • Develop AI-driven anomaly detection and prediction for integration and API behavior, including error spikes and latency patterns, with human-in-the-loop controls for remediation actions.
  • Optimize and analyze scripts used in integration flows for performance and maintainability using AI-assisted code analysis techniques.
  • Build automated integration testing strategies, including schema and contract validation, payload regression suites, replay testing, and API testing tool-driven verification.
  • Implement AI evaluation harnesses using offline golden test sets and online monitoring for generated mappings, flows, and operational recommendations.
  • Establish release gates for integration changes and AI prompt and tool updates to prevent silent degradation.
  • Set up monitoring dashboards and alerts for flows, APIs, and event-driven pipelines, and establish traceability through correlation IDs and end-to-end tracking.
  • Diagnose and resolve integration issues using structured logs, message traces, and failure-mode analysis.
  • Create AI-native operational experiences such as conversational root-cause analysis, runbook-guided remediation, and impact analysis, bounded by role-based access and approval workflows.
  • Apply integration advisory practices to design hybrid integration platforms and define integration best practices across teams.
  • Use integration assessment approaches to improve integration maturity, standardize patterns, and automate repeatable architectural governance where feasible.

Desired Qualifications

  • Experience with event-driven integration design and enterprise messaging patterns.
  • Experience with connector-based integrations across third-party SaaS ecosystems.
  • Experience migrating and modernizing legacy integration platforms to cloud integration.
  • Experience with integration governance and advisory methodologies for enterprise-wide standardization.

About the Company

Accenture

Advises businesses and runs their technology

Accenture advises large businesses and public agencies on strategy, builds their technology systems and runs ongoing operations. Its teams connect business planning with implementation, covering areas such as cloud migration, cybersecurity and customer experience. Consultants work with clients to redesign processes, while engineers integrate software from technology partners and maintain the resulting systems for multinational organizations. Clients pay for project work or continuing services, including application support and business processes such as finance and customer service. Accenture was founded in 1989 and has its headquarters in Dublin, Ireland.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1989

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