Senior AI Data Engineer

Role overview

You will join Elastic as a Senior AI Data Engineer to build and maintain a trusted customer data foundation for Sales. The work focuses on unifying fragmented GTM/customer data into an AI-ready dataset, partnering with RevOps, GTM systems, and field stakeholders.

Key missions

• Build and maintain the gold customer dataset by designing a canonical dataset that unifies signals from multiple systems.
• Work with RevOps Data Science to prepare both structured and unstructured data for downstream AI workflows.
• Implement data monitoring, drift detection, and data lineage so anomalies are detected before reaching forecasting/previsonnal use.
• Ensure data governance, consent management, and responsible AI practices.

Responsibilities

• Transform messy CRM/GTM data into a clean, enriched, AI-ready form.
• Support downstream ML/LLM pipelines with properly prepared datasets.
• Collaborate with multiple GTM-related teams to improve data accuracy and entity consistency.

Requirements

• Experience making data AI-ready for RAG, embeddings, and AI agents (including chunking strategies, metadata enrichment, and embedding model selection).
• 3+ years building production pipelines that feed ML or LLM-based systems.
• Strong applied LLM usage for extraction, classification, and normalization, including the ability to evaluate model performance.
• Python and senior-level SQL.
• Cloud infrastructure experience (AWS, Azure, or GCP) and orchestration (Airflow, Dagster, or equivalent).
• GTM/CRM data fluency at scale (accounts, contacts, opportunities, leads), including entity resolution and deduplication.
• Familiarity with Elasticsearch, vector search, and ESRE (or strong interest in building with them).
• B.S./M.S. in Computer Science, Data Engineering, or related field.
• Prior experience in RevOps, GTM Systems, or Marketing Operations engineering teams.

Nice-to-haves

• Experience/knowledge in search and vectorization using the Elastic Stack.