Senior AI Data Engineer

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale , unleashing the potential of businesses and people.

Every forecast, territory plan, and customer conversation at Elastic depends on the quality of our customer data. We're looking for a Senior AI Engineer to join the RevTech Engineering team inside Revenue Operations and shape the data foundation our Sales teams rely on.

Our customer data lives across Salesforce, marketing automation, billing, product telemetry, and support systems. Each has its own definitions, gaps, and drift. This role turns that fragmented reality into a trusted, enriched, AI-ready dataset , and keeps it that way as Elastic scales.

Responsibilities

• Build and maintain the golden customer dataset. Design the canonical dataset that unifies signals from across GTM systems into a single, governed source of truth , including the enrichment pipelines, deduplication, entity resolution, and validation systems that keep it accurate as sources land and drift.
• Make data AI-ready. Work with the RevOps Data Science team to prepare structured and unstructured data for downstream AI workflows , account research, lead scoring, churn signals, CSM briefings , covering chunking, embedding strategy, metadata design, and source integration across GTM systems, product telemetry, and third-party enrichment providers.
• Own quality and lineage. Implement monitoring, drift detection, and lineage tracking so anomalies surface before they reach a forecast, a dashboard, or a seller's inbox.
• Set the standard. Define how RevTech prepares data for AI consumption and document the schemas, pipelines, and contracts downstream teams depend on.

Requirements

• 3+ years of experience building production pipelines that feed ML or LLM-based systems.
• GTM data fluency. You've worked with CRM data at scale , accounts, contacts, opportunities, leads , and understand the entity resolution and deduplication challenges that come with it.
• AI-readiness experience. You've prepared data for RAG, embeddings, and AI agents, including chunking strategies, metadata enrichment, and embedding model selection.
• LLM applied to data. You've used LLMs for extraction, classification, and normalization , and you know how to evaluate whether they're working.
• Core tools. Python, senior-level SQL, and cloud infrastructure (AWS, Azure, or GCP) with orchestration experience (Airflow, Dagster, or equivalent).
• Elastic Stack. Working knowledge of Elasticsearch, vector search, and ESRE , or genuine interest in building it.

Benefits

• Competitive pay based on the work you do here and not your previous salary
• Health coverage for you and your family in many locations
• Ability to craft your calendar with flexible locations and schedules for many roles
• Generous number of vacation days each year
• Increase your impact - We match up to $2000 (or local currency equivalent) for financial donations and service
• Up to 40 hours each year to use toward volunteer projects you love
• Embracing parenthood with minimum of 16 weeks of parental leave