14 days ago
Bengaluru, IndiaStaff+
Responsibilities
- Design and build scalable LLM-powered applications, intelligent assistants, AI copilots, RAG pipelines, and agentic or multi-agent workflows.
- Develop production-grade AI application code spanning data ingestion, embeddings, orchestration, APIs, evaluation harnesses, and model optimization.
- Build agentic workflows on SAP AI Core and integrate LLM features into CAP/Fiori applications using Python and Java.
- Architect and deploy multi-tenant SaaS solutions on SAP BTP and contribute to ontology-grounded enterprise agents.
- Establish LLMOps practices for deployment, monitoring, observability, governance, guardrails, evaluation, and benchmarking.
- Instrument OpenTelemetry tracing, build Cloud Logging dashboards, and optimize latency, throughput, inference costs, and HANA Cloud queries.
- Apply monitoring, alerting, incident response, and root cause analysis practices based on SRE principles.
- Contribute to proofs of concept, reusable AI solutions, technical publications, patent ideation, code reviews, and engineering mentorship.
Requirements
- 10–12 years of hands-on experience in AI/ML, generative AI, data science, and/or enterprise architecture delivering production-grade LLM and AI solutions.
- Degree in Computer Science, AI, Data Science, Engineering, or a related field.
- Expert-level Python skills for AI pipelines, agent frameworks, orchestration, APIs, and evaluation systems.
- Working knowledge of Java and SAP CAP, including integrating AI features into CAP Java microservices.
- Strong SQL and HANA Cloud skills, including query optimization, analytical functions, and HANA-specific constructs.
- Experience with LLMs, foundation models, agentic AI, deep learning, prompt engineering, RAG, embeddings, semantic search, fine-tuning, model evaluation, and guardrails.
- Experience with LangChain, LlamaIndex, Semantic Kernel, Hugging Face, OpenAI APIs, vector databases, TensorFlow, PyTorch, and scikit-learn.
- Experience with distributed systems, microservices, APIs, scalable resilient applications, Kubernetes or Docker, and cloud AI platforms.
- Hands-on experience with SAP AI Core, SAP Generative AI Hub, SAP BTP, CAP, and SAP BTP multi-tenancy patterns such as MTX and IAS/AMS.
- Experience designing data pipelines and working with Spark, Databricks, and big-data ecosystems.
- Experience with testing, evaluation harnesses, version control, CI/CD pipelines, code reviews, asynchronous programming, and event-driven APIs.
- Preferred qualifications include open-source contributions, publications, patent filings, GenAI transformation, enterprise search, copilots, autonomous agent frameworks, responsible AI, AI security, cost management, and production benchmarking.
- Knowledge of SAP Business Data Cloud, data products, object storage, Delta Sharing, and semantic layers is advantageous.
Benefits
- SAP offers health and well-being support, flexible working models, inclusion initiatives, professional development, and ongoing learning opportunities.
- This is a regular full-time professional role with an expected travel requirement of 0–10%.
- The role is identified as hybrid, with additional location information listed as #LI-Hybrid.
- SAP provides accessibility accommodations and equal employment opportunity protections.
Tech Stack
Apache SparkAWSAzureDatabricksDockerGitGoogle Cloud PlatformJavaKubernetesPythonPyTorchscikit-learnSQLTensorFlow
Categories
About SAP
SAP builds enterprise application software and cloud services for finance, procurement, supply chain, human resources, and analytics, sold through subscriptions, licenses, and support. Its portfolio includes SAP S/4HANA, SAP Business Technology Platform, SAP Ariba, and SAP SuccessFactors. Founded in 1972 and headquartered in Walldorf, Germany, SAP is a public company listed on the NYSE and Frankfurt (ETR) and serves enterprises and public-sector organizations worldwide.