- Develop and deploy LLM-based solutions and RAG architectures that solve real business problems
- Contribute to the end-to-end lifecycle of AI features: problem framing, data preparation, modeling, evaluation, deployment, and monitoring
- Work with existing data pipelines for preprocessing, feature extraction, and model inference
- Integrate AI solutions into the company's cloud infrastructure, ensuring scalability, security, and performance
- Collaborate with cross-functional squads to embed AI capabilities into products and internal tools
- Use AI coding tools (e.g. Cursor, Claude Code, GitHub Copilot) as a standard part of your development workflow
- Contribute to identifying where AI can add measurable value to business processes and products
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