Principal Data Scientist/ AI Application Development Expert
SAP Labs · Bangalore · 14+ yrs experience · Posted 2026-05-21
Tech stack: AWS, Azure, Docker, GCP, Kubernetes, Python, SQL
About the role
What You Build
Lead architecture and delivery of enterprise‑grade AI/ML and Generative AI solutions, including LLM‑powered applications, intelligent assistants, and AI copilots.
Define the enterprise AI/GenAI strategy aligned to business transformation, and evaluate emerging foundation models, frameworks, and technologies.
Design and implement scalable LLM applications and agentic systems using commercial and open‑source models; integrate vector databases, semantic search, prompt orchestration, tool/function calling, memory, and context‑aware reasoning.
Responsibilities:
- What You Build
- Lead architecture and delivery of enterprise‑grade AI/ML and Generative AI solutions, including LLM‑powered applications, intelligent assistants, and AI copilots.
- Define the enterprise AI/GenAI strategy aligned to business transformation, and evaluate emerging foundation models, frameworks, and technologies.
- Design and implement scalable LLM applications and agentic systems using commercial and open‑source models; integrate vector databases, semantic search, prompt orchestration, tool/function calling, memory, and context‑aware reasoning.
Qualifications:
- 14+ years in Data Science, AI/ML, Generative AI, and Enterprise Architecture with a track record delivering production‑grade LLM solutions.
- Degree in Computer Science, AI, Data Science, Engineering, or related field; PhD preferred for research‑intensive profiles.
- Technical expertise:
- AI/ML: Deep learning, LLMs, Generative AI/foundation models, NLP/conversational AI, predictive analytics, recommendation systems; reinforcement learning (preferred).
- LLM & GenAI: Prompt engineering/optimization, RAG, AI agents/multi‑agent systems, embeddings/semantic search, fine‑tuning/adaptation, model evaluation/guardrails, LLMOps and observability.
- Frameworks & Tools: LangChain, LlamaIndex, Semantic Kernel, Hugging Face, OpenAI APIs; vector databases (Pinecone, Weaviate, ChromaDB, FAISS); TensorFlow, PyTorch, scikit‑learn.
- Architecture & Platforms: Enterprise/solution architecture, distributed systems, microservices/APIs, cloud AI (AWS, Azure, GCP, SAP BTP), Kubernetes/Docker, CI/CD for AI.
- Programming & Data: Python, SQL, R; Spark/Databricks; data engineering and big‑data ecosystems.
- Preferred:
- Publications, patents, open‑source contributions, innovation/incubator or R&D experience.
- Hands‑on in GenAI transformation, enterprise search, copilots, or autonomous agents.
- Strong understanding of Responsible AI, governance, and AI security.
- Core strengths:
- Strategic, innovation‑driven mindset; excellent problem‑solving.
- Clear communication and executive‑level storytelling.
- Influence across senior leadership and customers; commitment to continuous learning.
- Success measures:
- Scalable AI/LLM solutions in production with measurable business impact.
- Innovation outcomes (adoption, reusability), research/patent contributions.
- Platform maturity: governance, reliability, cost/perf efficiency.
- Team capability growth and mentorship outcomes.
- Where You Belong
- Join SAP’s PCP Cross Technology and Architecture unit—part of Private Cloud Products—driving technologies that empower innovation in business and for people.
- Be part of a dynamic, mission‑driven team using AI to enable seamless interactions between individuals and information.
- Work in a collaborative, learning‑oriented culture that values diverse perspectives and encourages experimentation.
- Thrive in a global, inclusive environment with opportunities to partner across regions and disciplines.
Qualifications
- 14+ years in Data Science, AI/ML, Generative AI, and Enterprise Architecture with a track record delivering production‑grade LLM solutions.
- Degree in Computer Science, AI, Data Science, Engineering, or related field; PhD preferred for research‑intensive profiles.
- Technical expertise: AI/ML:
- Deep learning, LLMs, Generative AI/foundation models, NLP/conversational AI, predictive analytics, recommendation systems; reinforcement learning (preferred).
- LLM & GenAI: Prompt engineering/optimization, RAG, AI agents/multi‑agent systems, embeddings/semantic search, fine‑tuning/adaptation, model evaluation/guardrails, LLMOps and observability.
- Frameworks & Tools: LangChain, LlamaIndex, Semantic Kernel, Hugging Face, OpenAI APIs; vector databases (Pinecone, Weaviate, ChromaDB, FAISS); TensorFlow, PyTorch, scikit‑learn.
- Architecture & Platforms: Enterprise/solution architecture, distributed systems, microservices/APIs, cloud AI (AWS, Azure, GCP, SAP BTP), Kubernetes/Docker, CI/CD for AI.
- Programming & Data: Python, SQL, R; Spark/Databricks; data engineering and big‑data ecosystems.
- Publications, patents, open‑source contributions, innovation/incubator or R&D experience.
- Hands‑on in GenAI transformation, enterprise search, copilots, or autonomous agents.
- Strong understanding of Responsible AI, governance, and AI security.
- Core strengths: Strategic, innovation‑driven mindset; excellent problem‑solving.
- Clear communication and executive‑level storytelling.
- Influence across senior leadership and customers; commitment to continuous learning.
- Success measures: Scalable AI/LLM solutions in production with measurable business impact.
- Innovation outcomes (adoption, reusability), research/patent contributions.
- Platform maturity: governance, reliability, cost/perf efficiency.
- Team capability growth and mentorship outcomes.
- Where You Belong
- Join SAP’s PCP Cross Technology and Architecture unit—part of Private Cloud Products—driving technologies that empower innovation in business and for people.
- Be part of a dynamic, mission‑driven team using AI to enable seamless interactions between individuals and information.
- Work in a collaborative, learning‑oriented culture that values diverse perspectives and encourages experimentation.
- Thrive in a global, inclusive environment with opportunities to partner across regions and disciplines.
Responsibilities
- What You Build
- Lead architecture and delivery of enterprise‑grade AI/ML and Generative AI solutions, including LLM‑powered applications, intelligent assistants, and AI copilots.
- Define the enterprise AI/GenAI strategy aligned to business transformation, and evaluate emerging foundation models, frameworks, and technologies.
- Design and implement scalable LLM applications and agentic systems using commercial and open‑source models; integrate vector databases, semantic search, prompt orchestration, tool/function calling, memory, and context‑aware reasoning.