Develop and operate enterprise integrations using SAP BTP Integration Suite across cloud, on-premise, and hybrid environments. Build iFlows, mappings, transformations, APIs, connectors, event-driven integrations, monitoring, and automated tests. Create AI-native integration capabilities including flow generation, retrieval-grounded recommendations, anomaly detection, evaluation harnesses, and conversational troubleshooting with appropriate safety controls. Support integration governance, modernization, reliability, and enterprise-wide standardization.
Project Role : AI Native Software Engineer
Project Role Description : Build and ship production-ready software using AI as a core part of the engineering lifecycle. Apply AI-native practices to develop and validate solutions, maintain quality and compliance, and continuously improve how software is built and operated.
Must have skills : SAP BTP Integration Suite
Good to have skills : SAP PO/PI & APIs Development
Minimum 5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary
AI Powered Tech Talent
Build AI native, enterprise integration products on SAP BTP Integration Suite by combining strong integration engineering fundamentals with agentic AI patterns (LLMs + tools + retrieval + evaluation). The role focuses on creating and operating production-grade integrations across cloud, on premise, and hybrid landscapes—while augmenting the integration lifecycle with intelligent capabilities such as automated iFlow generation, mapping recommendations, anomaly detection, predictive operations, and conversational troubleshooting. This role owns AI behavior in the integration layer (grounding, safety, evaluation), not just AI-assisted development.
Core Responsibilities
1) Integration Engineering (Cloud, Hybrid, On Prem)
Design, develop, and run end-to-end integration scenarios using cloud integration capabilities, enabling reliable connectivity across SAP and non SAP systems.
Build, structure, and manage large integration flows with clear modularity, reusability, and maintainability for enterprise scale.
2) Integration Flow Development (iFlows) & Message Transformation
Create and maintain integration flows using routing, splitting, gathering, and other transformation patterns.
Implement message mappings and data transformations for common enterprise formats (e.g., JSON, XML, CSV), ensuring semantic correctness and downstream compatibility.
Apply canonical modeling and contract-first practices to reduce brittle point-to-point dependencies.
3) Scripting, Persistence & Advanced Flow Control
Use scripting (e.g., Groovy) to implement complex transformation logic, enrichment, validation, and conditional execution paths.
Implement message persistence patterns (e.g., data stores) to support idempotency, retries, correlation, and resilience.
4) API & Connector Enablement
Design and expose secure APIs through API management capabilities (policies, authentication/authorization, throttling, versioning).
Integrate with third party applications using connector-based approaches and standardized integration patterns.
Enable event-driven integration approaches using messaging/event capabilities for near real-time propagation and decoupled architectures.
5) AI Native Integration Intelligence (Agentic Integration Layer)
Build integration agents that can generate initial iFlows from system/endpoint selections and naming conventions, then validate them against enterprise standards.
Implement retrieval-grounded assistance that pulls from interface catalogs, mapping specs, standards, runbooks, and known incident patterns to produce verifiable recommendations (no free-form guessing).
Apply intelligent recommendations for mapping and configuration, accelerating build and reducing rework.
Develop AI-driven anomaly detection and prediction for integration/API behavior (error spikes, latency patterns), with human-in-the-loop controls for remediation actions.
Optimize and analyze scripts used in integration flows for performance and maintainability through AI-assisted code analysis techniques.
6) Testing, Quality Engineering & Evaluation Loops
Build automated testing strategies for integrations: schema/contract validation, payload regression suites, replay testing, and API testing tool-driven verification.
Implement AI evaluation harnesses (offline golden test sets + online monitoring) for generated mappings, generated flows, and operational recommendations.
Establish release gates for both integration changes and AI prompt/tool updates to prevent silent degradation.
7) Monitoring, Troubleshooting & Observability
Set up monitoring dashboards and alerts for flows, APIs, and event-driven pipelines establish traceability with 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.
8) Integration Strategy & Maturity Enablement
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.
Primary Skills (AI Native Must Have)
Strong hands-on expertise with SAP BTP Integration Suite concepts and building blocks (cloud integration/iFlows, transformation patterns, monitoring).
Proven ability to implement message mappings, routing patterns, and transformation logic across enterprise data formats.
Practical scripting capability (e.g., Groovy) for advanced integration flow customization and performance tuning.
Solid API design and management fundamentals (security, throttling, lifecycle/versioning, observability).
AI-native delivery capability: tool-augmented workflows, retrieval-grounded outputs, measurable evaluation loops, and safe action boundaries.
Secondary / Strongly Beneficial Skills
Event-driven integration design and enterprise messaging patterns.
Connector-based integrations with third-party SaaS ecosystems.
Migration and modernization experience from legacy integration platforms to cloud integration.
Integration governance and advisory methodologies for enterprise-wide standardization.
What This Role Does Not Center On
Training or fine-tuning foundation models from scratch.
AI-assisted only integration work this role builds and owns AI behavior in the integration layer (grounding, evaluation, guardrails, observability).
Value Delivered
Faster integration delivery via intelligent flow generation, mapping recommendations, and script optimization.
Higher reliability and lower run cost via anomaly detection, predictive operations, and grounded troubleshooting.
Scalable integration landscapes through standardized patterns, governance, and maturity enablement.
Additional Information
A 15 years full time education is required15 years full time education
Project Role Description : Build and ship production-ready software using AI as a core part of the engineering lifecycle. Apply AI-native practices to develop and validate solutions, maintain quality and compliance, and continuously improve how software is built and operated.
Must have skills : SAP BTP Integration Suite
Good to have skills : SAP PO/PI & APIs Development
Minimum 5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary
AI Powered Tech Talent
Build AI native, enterprise integration products on SAP BTP Integration Suite by combining strong integration engineering fundamentals with agentic AI patterns (LLMs + tools + retrieval + evaluation). The role focuses on creating and operating production-grade integrations across cloud, on premise, and hybrid landscapes—while augmenting the integration lifecycle with intelligent capabilities such as automated iFlow generation, mapping recommendations, anomaly detection, predictive operations, and conversational troubleshooting. This role owns AI behavior in the integration layer (grounding, safety, evaluation), not just AI-assisted development.
Core Responsibilities
1) Integration Engineering (Cloud, Hybrid, On Prem)
Design, develop, and run end-to-end integration scenarios using cloud integration capabilities, enabling reliable connectivity across SAP and non SAP systems.
Build, structure, and manage large integration flows with clear modularity, reusability, and maintainability for enterprise scale.
2) Integration Flow Development (iFlows) & Message Transformation
Create and maintain integration flows using routing, splitting, gathering, and other transformation patterns.
Implement message mappings and data transformations for common enterprise formats (e.g., JSON, XML, CSV), ensuring semantic correctness and downstream compatibility.
Apply canonical modeling and contract-first practices to reduce brittle point-to-point dependencies.
3) Scripting, Persistence & Advanced Flow Control
Use scripting (e.g., Groovy) to implement complex transformation logic, enrichment, validation, and conditional execution paths.
Implement message persistence patterns (e.g., data stores) to support idempotency, retries, correlation, and resilience.
4) API & Connector Enablement
Design and expose secure APIs through API management capabilities (policies, authentication/authorization, throttling, versioning).
Integrate with third party applications using connector-based approaches and standardized integration patterns.
Enable event-driven integration approaches using messaging/event capabilities for near real-time propagation and decoupled architectures.
5) AI Native Integration Intelligence (Agentic Integration Layer)
Build integration agents that can generate initial iFlows from system/endpoint selections and naming conventions, then validate them against enterprise standards.
Implement retrieval-grounded assistance that pulls from interface catalogs, mapping specs, standards, runbooks, and known incident patterns to produce verifiable recommendations (no free-form guessing).
Apply intelligent recommendations for mapping and configuration, accelerating build and reducing rework.
Develop AI-driven anomaly detection and prediction for integration/API behavior (error spikes, latency patterns), with human-in-the-loop controls for remediation actions.
Optimize and analyze scripts used in integration flows for performance and maintainability through AI-assisted code analysis techniques.
6) Testing, Quality Engineering & Evaluation Loops
Build automated testing strategies for integrations: schema/contract validation, payload regression suites, replay testing, and API testing tool-driven verification.
Implement AI evaluation harnesses (offline golden test sets + online monitoring) for generated mappings, generated flows, and operational recommendations.
Establish release gates for both integration changes and AI prompt/tool updates to prevent silent degradation.
7) Monitoring, Troubleshooting & Observability
Set up monitoring dashboards and alerts for flows, APIs, and event-driven pipelines establish traceability with 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.
8) Integration Strategy & Maturity Enablement
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.
Primary Skills (AI Native Must Have)
Strong hands-on expertise with SAP BTP Integration Suite concepts and building blocks (cloud integration/iFlows, transformation patterns, monitoring).
Proven ability to implement message mappings, routing patterns, and transformation logic across enterprise data formats.
Practical scripting capability (e.g., Groovy) for advanced integration flow customization and performance tuning.
Solid API design and management fundamentals (security, throttling, lifecycle/versioning, observability).
AI-native delivery capability: tool-augmented workflows, retrieval-grounded outputs, measurable evaluation loops, and safe action boundaries.
Secondary / Strongly Beneficial Skills
Event-driven integration design and enterprise messaging patterns.
Connector-based integrations with third-party SaaS ecosystems.
Migration and modernization experience from legacy integration platforms to cloud integration.
Integration governance and advisory methodologies for enterprise-wide standardization.
What This Role Does Not Center On
Training or fine-tuning foundation models from scratch.
AI-assisted only integration work this role builds and owns AI behavior in the integration layer (grounding, evaluation, guardrails, observability).
Value Delivered
Faster integration delivery via intelligent flow generation, mapping recommendations, and script optimization.
Higher reliability and lower run cost via anomaly detection, predictive operations, and grounded troubleshooting.
Scalable integration landscapes through standardized patterns, governance, and maturity enablement.
Additional Information
A 15 years full time education is required15 years full time education
About Accenture
Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.Visit us at www.accenture.com
Equal Employment Opportunity Statement
We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, military veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by applicable law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.
Accenture Airoli, Mahārāshtra, IND Office
Airoli, India
Accenture Mumbai, Maharashtra, IND Office
Ganpatrao Kadam Marg, off Senapati Bapat Marg, Lower Parel West, Lower Parel, Mumbai, Maharashtra, India, 400013
Similar Jobs
Information Technology
Design and architect scalable multi-agent AI systems using Microsoft AI Foundry, Semantic Kernel, AutoGen, Copilot Studio, and Azure AI services. Lead AI transformation initiatives, make architectural decisions, guide engineering and product teams, implement Responsible AI practices, mentor teams, and optimize solution scalability, accuracy, and compliance. The role also requires cross-functional collaboration, stakeholder engagement, and delivery of enterprise GenAI solutions.
Top Skills:
AutogenAzure Ai ServicesAzure Machine LearningAzure Openai ServiceAzure Platform As A Service (Paas)Copilot StudioLarge Language Models (Llms)Microsoft Ai FoundryAzurePythonSemantic KernelSmall Language Models (Slms)Visual Studio Code
Information Technology
Design and lead scalable multi-agent AI architectures using Microsoft AI Foundry, Semantic Kernel, AutoGen, Copilot Studio, and Azure AI services. Develop production-ready generative AI applications, integrate LLMs and SLMs, establish Responsible AI practices, and guide engineering teams on solution design, deployment, governance, and optimization. The role also involves architectural decision-making, stakeholder collaboration, mentoring, and technical training.
Top Skills:
AutogenAzure Ai ServicesAzure Machine LearningAzure Openai ServiceCopilot StudioLarge Language Models (Llms)Microsoft Ai FoundryPythonResponsible AiSemantic KernelSmall Language Models (Slms)Visual Studio Code
Information Technology
Develop and operate enterprise integrations on SAP BTP Integration Suite across cloud, on-premises, and hybrid environments. Build iFlows, message mappings, transformations, APIs, connectors, event-driven pipelines, monitoring, and automated testing. Use Groovy for advanced flow logic and implement persistence, resilience, and observability patterns. Develop AI-native integration capabilities including flow generation, grounded recommendations, anomaly detection, evaluation loops, conversational troubleshooting, and governance controls.
Top Skills:
Ai Evaluation HarnessesApi ManagementAPIsCsvEvent-Driven MessagingGroovyJSONLlmsRetrieval-Augmented GenerationSap Btp Integration SuiteSap Po/PiXML
What you need to know about the Mumbai Tech Scene
From haggling for the best price at Chor Bazaar to the bustle of Crawford Market, the energy of Mumbai's traditional markets is a key part of the city's charm. And while these markets will always have their place, the city also boasts a thriving e-commerce scene, ranking among the largest in the region. Driven by online sales in everything from snacks to licensed sports merchandise to children's apparel, the local industry is worth billions, with companies actively recruiting to meet the demands of continued growth.
