A

Accenture

Advises businesses and runs their technology

Custom Software Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listedIn-person

About the Job

Requirements

  • A minimum of 12 years of experience is required; additional information also specifies 16+ years of experience as a solution architect driving SAP BTP and Generative AI initiatives.
  • Completion of at least 15 years of full-time education and a Bachelor's or Master's degree in Computer Science, Information Technology, or Electronics and Communication from a recognized institution.
  • Deep understanding of SAP Business Technology Platform services, especially AI Core, Generative AI Hub, and HANA Cloud Vector Engine and Knowledge Graph Engine.
  • Expertise with Large Language Models, Foundation Models, and orchestration frameworks such as LangChain, LangGraph, or Semantic Kernel.
  • Hands-on experience designing Retrieval-Augmented Generation pipelines using embeddings, chunking, and vector similarity search.
  • Proficiency in Knowledge Graph design, GraphRAG, and ontology modeling using SAP HANA Cloud or graph databases.
  • Strong understanding of data grounding, semantic enrichment, and enterprise contextualization.
  • Experience with schema-based output parsing, prompt templating, prompt engineering best practices, and AI evaluation frameworks.
  • Familiarity with content filtering, data masking, and AI governance and compliance frameworks in enterprise environments.
  • Working knowledge of the Cloud Application Programming model and SAP Extension Suite for integrating Generative AI into enterprise applications.
  • Understanding of vector stores, vector search, and semantic search APIs in HANA Cloud.
  • Exposure to multi-tenant SaaS architecture, hyperscaler-agnostic deployments, and MLOps pipelines for AI solutions.
  • Experience deploying large-scale SAP applications, infrastructure, data, integrations, and related systems.
  • Expertise in application design principles, cloud-native development, and integration within the SAP ecosystem.
  • Familiarity with integration techniques and tools within the SAP ecosystem.
  • Strong understanding of application design principles and methodologies.
  • Ability to align AI capabilities with business objectives while ensuring scalability, responsible use, and tangible value realization.
  • Ability to analyze and optimize application performance.
  • Experience in agentic development using the A2A protocol with an MCP server.
  • Working knowledge of RDF, SPARQL, OWL, or equivalent graph technologies.
  • Familiarity with Docker, Kubernetes, and CI/CD automation tools such as GitHub Actions, Jenkins, or SAP Continuous Integration and Delivery.
  • Knowledge of observability tools such as Prometheus and Grafana, and tracing AI requests through pipelines.
  • Experience deploying AI workloads using Terraform, BTP CLI, or Kyma Runtime automation.
  • Awareness of Responsible AI principles, including transparency, explainability, fairness, and privacy.
  • Ability to translate business processes into AI-driven workflows, integrating Agentic AI patterns and SAP AI services.
  • Strategic thinking, client-focused articulation, and effective demonstration and communication experience.

Responsibilities

  • Lead AI-driven solution design and delivery using Generative and Agentic AI to solve complex business problems, automate processes, and integrate intelligent insights into enterprise operations for measurable impact.
  • Serve as a subject matter expert for SAP BTP and Generative AI solutions.
  • Build technical architecture designs aligned with SAP and enterprise standards.
  • Architect and implement Generative AI pipelines on SAP BTP using SAP AI Core, Generative AI Hub, and SAP HANA Cloud Vector Engine and Knowledge Graph Engine.
  • Design and manage RAG and GraphRAG workflows to improve the grounding, accuracy, and interpretability of Large Language Model outputs.
  • Integrate Large Language Models and Foundation Models with enterprise data sources through grounding modules, vector similarity search, and semantic search.
  • Build Knowledge Graphs and ontologies to model enterprise domains and link contextual data for reasoning and relationship-aware Generative AI applications.
  • Develop LangChain- or LangGraph-based orchestration pipelines for prompt templating, retrieval, generation, and post-processing.
  • Implement data masking, content filtering, and schema-based output parsing to ensure compliance, privacy, and structured response formats.
  • Collaborate with development teams using the SAP Cloud Application Programming model to embed AI capabilities into cloud-native applications.
  • Work with multitenant SaaS architectures, ensuring secure tenant isolation and hyperscaler-agnostic deployments.
  • Use chunking, embedding generation, and vector store management to enable efficient information retrieval and contextualization.
  • Optimize orchestration pipelines for prompt templating, query rewriting, and fusion techniques such as Reciprocal Rank Fusion to improve retrieval precision.
  • Lead the end-to-end lifecycle of Generative AI projects, from model integration and fine-tuning in AI Core through deployment, monitoring, and continuous improvement.
  • Collaborate with and manage cross-functional teams to deliver solutions on time and within scope.
  • Map business requirements to AI-powered solution architectures.
  • Mentor and upskill team members through knowledge-sharing sessions and best-practice frameworks.
  • Ensure scalability, performance, and responsible AI principles are embedded throughout the development lifecycle.
  • Track and report project progress, ensuring alignment with business objectives.
  • Transform SAP business processes with AI and introduce Agentic AI innovations in the SAP space.
  • Integrate Agentic AI patterns and SAP AI services to deliver scalable, intelligent, and automation-ready applications.
  • Own implementation from data and model integration through solution architecture, development, testing, and deployment within SAP landscapes and customer environments.
  • Collaborate with product, engineering, data, and customer teams to drive AI adoption, optimize models in production, and continuously improve solution quality and impact.

Desired Qualifications

  • Experience with Business Process Management and tools such as Signavio.
  • SAP certifications are preferred, specifically SAP Certified Associate – Positioning SAP Business AI Solutions as part of SAP Business Suite.
  • A fair understanding of AI technologies and their influence on business processes for functional and industry roles.

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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