Role overview
Circle has grown to $50M in ARR with a strong inbound motion. Now we're building the data and AI infrastructure to make our sales team 10x more effective through intelligent automation, real-time analytics, and custom-built AI applications.
This role sits on our Data & RevOps team and is equal parts analytics engineer, AI application developer, and sales force multiplier. You will directly support and collaborate with our sales team to help launch AI solutions that accelerate acquisition and expansion of revenue. You'll build production-grade data pipelines, design AI-powered sales tools, and create analytics systems that turn data into actionable insights for our go-to-market teams.
If you're obsessed with building elegant solutions that blend data engineering, modern AI tooling, and deep GTM intuition, this is your role.
What you'll work on
- Strong alignment with Circle's values
- CEFR Level C2 / ILR Level 5 proficiency in English (spoken, written, and reading)
- Strong Python skills — comfortable building production applications, working with APIs, data manipulation (pandas, polars), and AI/LLM libraries (OpenAI, Anthropic, LangChain, etc.)
- Advanced SQL and data modeling expertise — you can design dimensional models, write complex analytical queries, and build dbt projects from scratch
- Experience shipping AI applications — whether with LLM APIs, agent frameworks (such as N8N, Relevance, ClayAgents, or custom GPTs with MCP), or rapid prototyping tools like Lovable, Cursor, v0, or Replit. Prior experience deploying multi-agent systems will be an advantage.
- Proficiency with modern data tooling — dbt, data warehouses (Snowflake/BigQuery/Redshift), orchestration tools (Airflow/Dagster), and BI platforms (Looker/Tableau/Hex), and data enrichment tools such as Clay, Breeze, Apollo, etc.
- Deep understanding of GTM operations — you've worked closely with sales teams and understand lead scoring, pipeline analytics, territory planning, and sales workflows
- Strong systems thinking — you build for scale, maintainability, and reliability. You think about data quality, monitoring, and error handling from day one.
- Excellent communication skills — you can translate complex technical concepts into business value and collaborate effectively with non-technical stakeholders