Technology Architect
Technology Architecture Associate Director
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Full time
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Experience: 12-14 years
Job No. ATCI-5807218-S2072811
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Mumbai
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Required Skill: SAP BTP Application Development
Project Role : Technology Architect
Project Role Description : Design and deliver technology architecture for a platform, product, or engagement. Define solutions to meet performance, capability, and scalability needs.
Must have skills : SAP BTP Application Development
Good to have skills : Python (Programming Language), Node.js
Minimum 18 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
The SAP Business AI Development Manager leads the design, engineering, and delivery of responsible, scalable AI solutions on SAP Business Technology Platform (SAP BTP). The role combines hands-on SAP architecture and development expertise with engineering leadership, delivery governance, and stakeholder management. The manager will embed AI and generative AI capabilities into enterprise processes across SAP S/4HANA, SAP SuccessFactors, SAP Ariba, SAP Concur, supply chain, spend, and customer-experience solutions while maintaining clean-core, security, privacy, and responsible-AI standards.
SAP BTP Development Manager
SAP Business Technology Platform ,AI Engineering ,Generative AI ,Enterprise Application Development
Role: SAP BTP & Business AI Development Manager, Architect
Roles & Responsibilities:
Solution strategy and architecture: Define solution approaches and reference architectures for embedded and side-by-side AI extensions on SAP BTP, balancing business value, scalability, security, maintainability, and clean-core principles.
Engineering leadership: Lead multidisciplinary teams of AI engineers, SAP BTP developers, data engineers, integration specialists, and quality engineers plan capacity, allocate work, remove delivery impediments, and coach team members.
AI Foundation delivery: Govern development using SAP AI Core, SAP AI Launchpad, and the generative AI hub, covering experimentation, model selection, deployment, inference, monitoring, and continuous improvement.
Generative AI adoption: Establish standards for prompt engineering, prompt lifecycle management, model evaluation, retrieval-augmented generation, vector search, grounding, and rapid prototyping.
Business-process integration: Embed capabilities such as intelligent document processing, natural-language interfaces, workflow automation, recommendations, forecasting, and decision support into SAP and non-SAP processes.
Application development: Oversee SAP CAP, ABAP Cloud, SAP Fiori/UI5, OData, SAP HANA Cloud, Cloud Foundry, and Kyma-based development, including APIs, events, integrations, and reusable services.
AI-assisted engineering: Guide responsible use of Joule for Developers and SAP Build Code for code scaffolding, explanation, refactoring, test generation, and review support.
Quality and DevSecOps: Ensure AI-generated and developer-created artifacts are reviewed, validated, tested, secured, traceable, and approved before release drive CI/CD, observability, automated testing, and production-support practices.
Responsible AI and governance: Implement controls for privacy, security, transparency, content safety, bias mitigation, human oversight, model risk, auditability, and regulatory compliance throughout the AI lifecycle.
Capability building: Create engineering standards, reusable accelerators, reference implementations, and learning plans that strengthen AI, application development, integration, analytics, and data-engineering capabilities.
Professional & Technical Skills:
Hands-on experience with SAP BTP and relevant services, including SAP AI Core, SAP AI Launchpad, the generative AI hub, SAP HANA Cloud, SAP Build Code, and SAP Integration Suite.
Strong knowledge of generative AI, large language models, retrieval-augmented generation, embeddings, vector search, prompt engineering, model evaluation, and AI observability.
Proficiency in one or more SAP development stacks: SAP CAP with Node.js or Java, ABAP Cloud, SAP Fiori/UI5, OData, REST APIs, and event-driven integration.
Experience designing cloud-native applications and microservices on Cloud Foundry and,or Kyma,Kubernetes, supported by Git, CI,CD, automated testing, and secure DevOps practices.
Good understanding of SAP BTP security, including identity and access management, OAuth, role-based access, secrets management, data protection, and secure API design.
Working knowledge of AI-enabled business processes in SAP S/4HANA and one or more SAP cloud applications such as SuccessFactors, Ariba, Concur, Sales Cloud, or Signavio.
Demonstrated ability to convert business opportunities into solution designs, delivery plans, estimates, risks, controls, and measurable outcomes.
Strong people leadership, stakeholder management, communication, problem-solving, and delivery ownership.
Preferred Qualifications
SAP certification in BTP application development, integration, data, analytics, AI engineering, or a related specialization.
Experience with SAP Joule Studio and the design or orchestration of AI agents.
Experience with SAP Document AI, SAP Build Process Automation, Event Mesh, and asynchronous architectures.
Knowledge of SAP HANA Cloud Predictive Analysis Library, Automated Predictive Library, and vector capabilities.
Experience integrating models and services from Hyperscaler or SAP AI ecosystem partners through governed enterprise patterns.
Experience delivering AI solutions in regulated environments with privacy, security, data residency, and compliance obligations.
Familiarity with responsible-AI frameworks, model risk management, evaluation benchmarks, red teaming, and human-in-the-loop controls.
Experience creating reusable assets, engineering playbooks, and communities of practice for enterprise AI adoption.
Leadership Competencies
Strategic orientation: Connect AI investments to business outcomes, adoption, and value realization.
Technical judgment: Make pragmatic build, buy, reuse, and integration decisions across SAP and partner services.
Delivery leadership: Manage scope, quality, schedule, cost, dependencies, and operational readiness across concurrent workstreams.
Talent development: Build high-performing teams through coaching, feedback, knowledge sharing, and structured capability development.
Executive communication: Explain complex AI concepts, design trade-offs, risks, and value in clear business language.
Collaboration and ownership: Work effectively across business, architecture, engineering, data, security, legal, risk, and operations teams.
Measures of Success
AI use cases delivered on time, within agreed quality and risk thresholds, and with measurable business outcomes.
Production reliability, security, performance, adoption, and responsible-AI compliance of deployed solutions.
Reuse of approved architecture patterns, accelerators, components, and engineering standards.
Improvement in engineering productivity, automated test coverage, release quality, and time to value.
Stakeholder satisfaction and growth in the capability, proficiency, and retention of the engineering team.
Additional Information:
Bachelor s or master s degree in computer science, engineering, data science, information systems, or a related discipline.
Typically 10+ years of enterprise application or technology delivery experience, including 3+ years leading SAP BTP, AI/ML, data, or cloud engineering teams.
Project Role Description : Design and deliver technology architecture for a platform, product, or engagement. Define solutions to meet performance, capability, and scalability needs.
Must have skills : SAP BTP Application Development
Good to have skills : Python (Programming Language), Node.js
Minimum 18 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
The SAP Business AI Development Manager leads the design, engineering, and delivery of responsible, scalable AI solutions on SAP Business Technology Platform (SAP BTP). The role combines hands-on SAP architecture and development expertise with engineering leadership, delivery governance, and stakeholder management. The manager will embed AI and generative AI capabilities into enterprise processes across SAP S/4HANA, SAP SuccessFactors, SAP Ariba, SAP Concur, supply chain, spend, and customer-experience solutions while maintaining clean-core, security, privacy, and responsible-AI standards.
SAP BTP Development Manager
SAP Business Technology Platform ,AI Engineering ,Generative AI ,Enterprise Application Development
Role: SAP BTP & Business AI Development Manager, Architect
Roles & Responsibilities:
Solution strategy and architecture: Define solution approaches and reference architectures for embedded and side-by-side AI extensions on SAP BTP, balancing business value, scalability, security, maintainability, and clean-core principles.
Engineering leadership: Lead multidisciplinary teams of AI engineers, SAP BTP developers, data engineers, integration specialists, and quality engineers plan capacity, allocate work, remove delivery impediments, and coach team members.
AI Foundation delivery: Govern development using SAP AI Core, SAP AI Launchpad, and the generative AI hub, covering experimentation, model selection, deployment, inference, monitoring, and continuous improvement.
Generative AI adoption: Establish standards for prompt engineering, prompt lifecycle management, model evaluation, retrieval-augmented generation, vector search, grounding, and rapid prototyping.
Business-process integration: Embed capabilities such as intelligent document processing, natural-language interfaces, workflow automation, recommendations, forecasting, and decision support into SAP and non-SAP processes.
Application development: Oversee SAP CAP, ABAP Cloud, SAP Fiori/UI5, OData, SAP HANA Cloud, Cloud Foundry, and Kyma-based development, including APIs, events, integrations, and reusable services.
AI-assisted engineering: Guide responsible use of Joule for Developers and SAP Build Code for code scaffolding, explanation, refactoring, test generation, and review support.
Quality and DevSecOps: Ensure AI-generated and developer-created artifacts are reviewed, validated, tested, secured, traceable, and approved before release drive CI/CD, observability, automated testing, and production-support practices.
Responsible AI and governance: Implement controls for privacy, security, transparency, content safety, bias mitigation, human oversight, model risk, auditability, and regulatory compliance throughout the AI lifecycle.
Capability building: Create engineering standards, reusable accelerators, reference implementations, and learning plans that strengthen AI, application development, integration, analytics, and data-engineering capabilities.
Professional & Technical Skills:
Hands-on experience with SAP BTP and relevant services, including SAP AI Core, SAP AI Launchpad, the generative AI hub, SAP HANA Cloud, SAP Build Code, and SAP Integration Suite.
Strong knowledge of generative AI, large language models, retrieval-augmented generation, embeddings, vector search, prompt engineering, model evaluation, and AI observability.
Proficiency in one or more SAP development stacks: SAP CAP with Node.js or Java, ABAP Cloud, SAP Fiori/UI5, OData, REST APIs, and event-driven integration.
Experience designing cloud-native applications and microservices on Cloud Foundry and,or Kyma,Kubernetes, supported by Git, CI,CD, automated testing, and secure DevOps practices.
Good understanding of SAP BTP security, including identity and access management, OAuth, role-based access, secrets management, data protection, and secure API design.
Working knowledge of AI-enabled business processes in SAP S/4HANA and one or more SAP cloud applications such as SuccessFactors, Ariba, Concur, Sales Cloud, or Signavio.
Demonstrated ability to convert business opportunities into solution designs, delivery plans, estimates, risks, controls, and measurable outcomes.
Strong people leadership, stakeholder management, communication, problem-solving, and delivery ownership.
Preferred Qualifications
SAP certification in BTP application development, integration, data, analytics, AI engineering, or a related specialization.
Experience with SAP Joule Studio and the design or orchestration of AI agents.
Experience with SAP Document AI, SAP Build Process Automation, Event Mesh, and asynchronous architectures.
Knowledge of SAP HANA Cloud Predictive Analysis Library, Automated Predictive Library, and vector capabilities.
Experience integrating models and services from Hyperscaler or SAP AI ecosystem partners through governed enterprise patterns.
Experience delivering AI solutions in regulated environments with privacy, security, data residency, and compliance obligations.
Familiarity with responsible-AI frameworks, model risk management, evaluation benchmarks, red teaming, and human-in-the-loop controls.
Experience creating reusable assets, engineering playbooks, and communities of practice for enterprise AI adoption.
Leadership Competencies
Strategic orientation: Connect AI investments to business outcomes, adoption, and value realization.
Technical judgment: Make pragmatic build, buy, reuse, and integration decisions across SAP and partner services.
Delivery leadership: Manage scope, quality, schedule, cost, dependencies, and operational readiness across concurrent workstreams.
Talent development: Build high-performing teams through coaching, feedback, knowledge sharing, and structured capability development.
Executive communication: Explain complex AI concepts, design trade-offs, risks, and value in clear business language.
Collaboration and ownership: Work effectively across business, architecture, engineering, data, security, legal, risk, and operations teams.
Measures of Success
AI use cases delivered on time, within agreed quality and risk thresholds, and with measurable business outcomes.
Production reliability, security, performance, adoption, and responsible-AI compliance of deployed solutions.
Reuse of approved architecture patterns, accelerators, components, and engineering standards.
Improvement in engineering productivity, automated test coverage, release quality, and time to value.
Stakeholder satisfaction and growth in the capability, proficiency, and retention of the engineering team.
Additional Information:
Bachelor s or master s degree in computer science, engineering, data science, information systems, or a related discipline.
Typically 10+ years of enterprise application or technology delivery experience, including 3+ years leading SAP BTP, AI/ML, data, or cloud engineering teams.
15 years full time education
Mumbai
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