Data Scientist

• Lead the design of AI systems that support complex, multi-step tasks, tool use, context adaptation, and intelligent decisions.
• Work closely with product and engineering to architect LLM-powered features that are robust, useful, and production-ready.
• Explore and implement RAG or Graph RAG approaches, including graph construction, entity linking, and hybrid scoring strategies.
• Design and implement LLM-powered systems for multi-step task automation, tool use, and context-aware reasoning.
• Contribute to prompt design and evaluate prompt results.
• Design and implement MLOps pipelines following best practices.
• Prototype, evaluate, and ship AI features using platforms like Claude or Amazon Bedrock with production readiness focus.
• Develop evaluation frameworks for model output quality, reliability, and alignment (e.g., hallucination detection, prompt regression, safety scoring).
• Embed AI capabilities into user workflows with engineers and designers to ensure meaningful product outcomes.
• Own the full lifecycle of AI components from evaluation and planning to testing, deployment, and continuous improvement.
• Contribute to AI strategy and roadmap to scale LLM usage responsibly across the platform.
• Collaborate closely with Principal Engineer to align AI workflows, system prompts, and model interaction layers.

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