AI and Data Engineer

What You Will Do

• Design and build a scalable platform and the data pipelines that ingest, transform, and serve structured and unstructured data to AI models
• Develop and iterate on AI/ML components — including LLM-based agents, embedding models, and behavioral simulation layers — that power synthetic persona generation
• Architect and maintain the data infrastructure underpinning persona modeling: feature stores, vector databases, data lakes, and real-time serving layers
• Collaborate with researchers to translate persona logic and behavioral frameworks into working system components
• Write production-quality code, participate in code reviews, and contribute to engineering standards for the team
• Monitor model and pipeline performance in production; identify and resolve issues proactively
• Contribute to system design discussions and help shape the technical roadmap

Core Technical Skills

• 3–5 years of hands-on experience in software engineering, data engineering, ML engineering, or a closely related role
• Proficiency in Python and at least one data processing framework (Spark, dbt, Airflow, Prefect, or similar)
• Experience building and deploying ML models or AI components in a production environment
• Familiarity with LLMs and modern AI tooling: prompt engineering, fine-tuning, RAG pipelines, or and agent frameworks (LangChain, LangGraph LlamaIndex, CrewAI, or equivalent)
• Solid understanding of data modeling, schema design, and the tradeoffs between different storage paradigms (relational, document, vector, columnar)
• Experience with cloud data infrastructure — AWS, GCP, or Azure — and comfort operating in a cloud-native environment

Systems & Engineering Mindset