Custom Software Engineer
About the job
- Minimum 12 years of experience is required.
- 15 years of full-time education with 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 SAP AI Core, Generative AI Hub, SAP 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 with embedding, 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, and AI evaluation frameworks.
- Familiarity with content filtering, data masking, and enterprise AI governance and compliance frameworks.
- Working knowledge of the Cloud Application Programming model and SAP Extension Suite.
- Understanding of vector stores, vector search, and semantic search APIs in SAP HANA Cloud.
- Exposure to multitenant SaaS architecture, hyperscaler-agnostic deployments, and MLOps pipelines.
- 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.
- Ability to analyze and optimize application performance.
- Experience with Agentic development using the A2A protocol and MCP servers.
- Working knowledge of RDF, SPARQL, OWL, or equivalent graph technologies.
- Familiarity with Docker, Kubernetes, and CI/CD automation using GitHub Actions, Jenkins, or SAP Continuous Integration and Delivery.
- Knowledge of observability tools such as Prometheus and Grafana, including tracing AI requests through pipelines.
- Experience deploying AI workloads with Terraform, BTP CLI, or Kyma Runtime automation.
- Awareness of responsible AI principles, including transparency, explainability, fairness, and privacy.
- Translate business processes into AI-driven workflows integrating SAP AI services.
- Own end-to-end implementation from data and model integration through solution architecture, development, testing, and deployment within SAP landscapes and customer environments.
- Collaborate cross-functionally with product, engineering, data, and customer teams to drive AI adoption, optimize models in production, and enhance solution quality and impact.
- Lead AI-driven solution design and delivery using Generative AI and Agentic AI to solve complex business problems, automate processes, and integrate intelligent insights into enterprise operations.
- Serve as a subject matter expert for SAP Business Technology Platform and Generative AI solutions.
- Build technical architecture designs aligned with SAP and enterprise standards.
- Architect and implement Generative AI pipelines on SAP Business Technology Platform using SAP AI Core, Generative AI Hub, and SAP HANA Cloud.
- Design and manage Retrieval-Augmented Generation and GraphRAG workflows to improve 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 and LangGraph orchestration pipelines for prompt templating, retrieval, generation, and post-processing.
- Implement data masking, content filtering, and schema-based output parsing for compliance, privacy, and structured response formats.
- Collaborate with development teams using the 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 using prompt templating, query rewriting, and fusion techniques such as Reciprocal Rank Fusion.
- Lead the end-to-end lifecycle of Generative AI projects, from model integration and fine-tuning in SAP 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 throughout the development lifecycle.
- Track and report project progress while maintaining strategic alignment with business objectives.
- Experience transforming SAP business processes with AI and infusing Agentic AI innovations into SAP environments.
- Experience in SAP Process AI and innovations within supply chain, finance, or industry domains.
- Experience with business process management and tools such as Signavio.
- Understanding of SAP standard AI features and setup.
- SAP certification, preferably SAP Certified Associate: Positioning SAP Business AI Solutions as part of SAP Business Suite.
About the company
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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Simplify's Take
What believers are saying
- Business demand grew: October 2026 results showed $74.2 billion annual revenue, up 5% in local currency.
- Eligible US employees buy discounted stock: Accenture's purchase plan sells shares at 15% below market price.
- Client relationships run deep: Accenture has worked with 195 of its top 200 customers for more than ten years.
What critics are saying
- Bookings are not guaranteed revenue: most Accenture contracts let clients cancel quickly with little or no penalty.
- Promotions require AI adoption: Accenture's CEO said in March 2026 that employees must use its tools effectively.
- Federal hiring practices proved costly: Accenture settled discrimination allegations for $25 million in September 2026, without a liability finding.
What makes Accenture unique
- Its AI platform switches models: AI Refinery selects among prebuilt models according to cost, performance and other requirements.
- Accenture owns specialist Microsoft expertise: it cofounded the Microsoft-focused Avanade consultancy with the software maker.
- Consulting includes creative agencies: Accenture Song owns businesses spanning advertising, digital product design and customer engagement.
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Benefits
Health Insurance
Professional Development Budget
401(k) Retirement Plan
401(k) Company Match
Company News
Accenture will hold an Investor Day on October 14, where it is expected to detail its long-term strategy, AI monetisation plans, growth guidance, and margin expansion goals. The event follows a rebound in its shares after fears that AI would erode traditional consulting work. The stock hit a low of $118.15 in June, down from a January high of $291.09. It has since gained nearly 77%, helped by fourth-quarter results on October 1 and an expanded collaboration with Dell Technologies. Fourth-quarter revenue rose 6% to $18.7 billion, and new bookings reached $22.2 billion. Accenture expects fiscal 2027 revenue growth of 3% to 6% in local currency. It raised its quarterly dividend by 5% to $1.71 per share, payable November 13, 2026. Its market capitalisation is about $139.6 billion.
Accenture has acquired Sagacity, a London-based data and customer intelligence firm, to strengthen Accenture Song's AI-powered customer services. The deal brings more than 140 professionals to Accenture Song's UK and Ireland operations. Terms were not disclosed. Founded in 2005 by Anita Dougall, Malka Townshend, and Harry Dougall, Sagacity offers data assets, AI-enabled technology, and customer intelligence expertise. Accenture says clients want to connect data, AI, and operations into unified programmes that deliver measurable results. The move targets industries with large customer bases, such as utilities, retail, banking, and telecommunications. "Sagacity's deep expertise and outcome-focused approach will enhance our ability to help clients turn insight into action," said Sohel Aziz, senior managing director of Accenture Song, UK and Ireland.
TM Forum has launched a multi-year Trustworthy AI programme with Accenture to help telecoms deploy autonomous operations with verifiable trust standards. The initiative will deliver the industry's first Trustworthy AI Governance Certification, providing a benchmark for trusted AI deployment. Recent TM Forum research found that whilst 72% of communications service providers believe their AI capabilities are trustworthy, only 14% can verify their claims. The programme aims to transform AI trust from aspiration into measurable operational capability. The certification will help organisations assess governance maturity, workforce readiness, and operational accountability needed to scale AI autonomously. It will operate through TM Forum's AI-Native Collaboration Studios, where telecoms operators, vendors, and partners will contribute real-world use cases to shape the framework.
Accenture reported revenue of nearly $74.2 billion for fiscal year 2026, up 6.5% year-over-year, with net income of roughly $8.5 billion. The professional services firm serves approximately 9,000 clients globally with 814,000 employees. Microsoft generated revenue of nearly $331.8 billion in FY 2026, a 17.8% increase, with net income of approximately $133.7 billion. The company's net margin reached close to 40.3%. Both companies maintained a debt-to-equity ratio of approximately 0.3x. Microsoft's free cash flow reached nearly $67.0 billion, whilst Accenture's was roughly $11.6 billion. Accenture recently addressed a $25 million settlement with the Department of Justice regarding federal contracting practices. Microsoft faces securities fraud class action lawsuits involving AI and Copilot claims, alongside antitrust scrutiny and an IRS tax audit.
Accenture shares surged 17% on Thursday after reporting strong fourth-quarter results. The company posted revenue of $18.7 billion, up 6% year-over-year, while earnings per share jumped 46% to $3.29. Management's full-year revenue growth forecast of 4.5% exceeded analyst expectations of 4%. Net bookings rose 4% to $22.2 billion. The company plans to return at least $9.5 billion to shareholders this financial year. However, TD Cowen analyst Bryan Bergin maintained a hold rating, citing concerns that the stock is fully priced at 15 times forward earnings. He cautioned that one strong quarter may represent a cyclical bounce rather than structural growth acceleration. Despite this, Wall Street remains optimistic, with a "moderate buy" consensus rating. Accenture currently offers a 3.05% dividend yield.