- What We Do
TRANSFORM
- Who We Serve
- Technologies
SAP
Data & Analytics
CAREERS
AI Data Analyst
Key Responsibilities
- Design, build, and deploy LLM-based applications including RAG pipelines, fine-tuned models, and multi-step agentic workflows
- Develop and expose AI capabilities as clean APIs using Flask or equivalent frameworks
- Own problems end-to-end — from scoping and prototyping to production deployment and monitoring
- Set up and maintain CI/CD pipelines to ensure reliable, repeatable model and service deployments
- Conduct applied research to evaluate new models, architectures, and techniques relevant to business needs
- Collaborate with product and business stakeholders to translate requirements into robust AI solutions
- Write clean, well-tested, and maintainable code that your teammates can build on
Skill Requirements
Core Technical Skills
- Strong proficiency in Python, including data manipulation, numerical computing, and software design patterns
- Solid foundations in Data Science and ML — statistics, model evaluation, feature engineering, experiment design
- Hands-on experience with LLMs (GPT, Claude, Mistral, Llama, etc.) including prompt engineering, context management, and output evaluation
- Practical experience building RAG systems — chunking strategies, vector stores, retrieval tuning, and grounding
- Experience with LLM fine-tuning techniques (instruction tuning, LoRA, PEFT) and understanding of when to fine-tune vs. prompt
- Familiarity with agentic AI patterns — tool-use, memory, orchestration frameworks (LangChain, LlamaIndex, AutoGen, etc.)
Engineering & Deployment
- Experience building and deploying REST APIs with Flask or similar frameworks
- Proficiency with CI/CD tools (GitHub Actions, GitLab CI, or similar) and deployment workflows
- Comfort with cloud platforms (AWS or Azure) for model hosting, storage, and serving
- Familiarity with containerization (Docker) and basic MLOps practices