1 day ago
Mumbai, India +3 moreStaff+
Responsibilities
- Lead AI-driven solution design and delivery using Generative AI and Agentic AI to automate processes and generate intelligent enterprise insights.
- Architect and implement Generative AI pipelines on SAP BTP using SAP AI Core, Generative AI Hub, SAP HANA Cloud Vector Engine, and Knowledge Graph Engine.
- Design RAG and GraphRAG workflows, including embedding generation, chunking, vector similarity search, semantic search, query rewriting, and retrieval fusion.
- Integrate LLMs and foundation models with enterprise data sources and build knowledge graphs and ontologies for contextual reasoning.
- Develop LangChain and LangGraph orchestration pipelines for prompting, retrieval, generation, post-processing, and evaluation.
- Implement data masking, content filtering, schema-based output parsing, AI governance, and responsible AI controls.
- Embed AI capabilities into cloud-native SAP applications using the CAP model and SAP Extension Suite.
- Design secure multitenant SaaS architectures and hyperscaler-agnostic deployments.
- Lead the GenAI project lifecycle from model integration and fine-tuning through deployment, monitoring, and continuous improvement.
- Map business requirements to AI solution architectures, collaborate with product, engineering, data, and customer teams, and report project progress.
- Manage and mentor cross-functional teams while ensuring scalability, performance, compliance, and measurable business impact.
Requirements
- At least 15 years of professional experience; the additional information identifies the Sr. Manager profile as requiring 16+ years of experience.
- Bachelor's or master's degree, such as B.E., B.Tech, BCA, or MCA, in Computer Science, IT, or Electronics and Communication, with at least 15 years of full-time education.
- Deep expertise in SAP BTP, SAP AI Core, Generative AI Hub, SAP HANA Cloud Vector Engine, and Knowledge Graph Engine.
- Hands-on experience with LLMs, foundation models, LLM orchestration, RAG, GraphRAG, vector search, semantic search, embeddings, chunking, and knowledge graphs.
- Experience with LangChain, LangGraph, or Semantic Kernel; CAP; SAP Extension Suite; multi-tenant SaaS; MLOps; and cloud-native application design.
- Experience transforming SAP business processes with AI, developing agentic solutions using A2A protocol and MCP servers, and working with SAP AI services.
- Working knowledge of RDF, SPARQL, OWL, graph technologies, AI evaluation frameworks, AI governance, content filtering, and data masking.
- Experience deploying large-scale SAP applications and AI workloads using Docker, Kubernetes, Terraform, BTP CLI, Kyma Runtime, and CI/CD automation.
- Familiarity with GitHub Actions, Jenkins, SAP Continuous Integration and Delivery, Prometheus, Grafana, and AI request tracing.
- SAP certification, including SAP Certified Associate - Positioning SAP Business AI Solutions as part of SAP Business Suite, is preferred.
- Ability to design scalable architectures, optimize application performance, align AI capabilities with business objectives, communicate with clients, and mentor team members.
Tech Stack
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About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.