Staff Data & AI Engineer

About the role

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 be doing

• Instrument and operationalize signal detection by building data pipelines that capture intent signals from community engagement, product usage, social platforms, and third-party tools (Common Room, Clay, etc.). Turn signals into scored, prioritized account lists, and help deploy scalable applications that utilize these signals to accelerate growth and improve our business
• Build and maintain the data backbone that powers GTME and Enablement AI solutions — ensuring clean data flow between HubSpot, data warehouse, enrichment providers, and custom-built applications.
• Build and maintain analytics infrastructure for sales operations — from data modeling and transformation pipelines (dbt, SQL) to real-time dashboards and reporting systems. Closely align with our RevOps Sales lead, and support building out our tracking systems.
• Design and ship AI-powered applications using Python, LLMs, and rapid development frameworks (Lovable, Cursor, v0, Replit) to automate sales workflows, personalize outreach, and surface intelligent insights.
• Own the full stack of sales analytics — from raw data ingestion to semantic layers to end-user applications. Build reliable, scalable systems that sales can depend on daily.
• Prototype and iterate rapidly on AI solutions — building agentic systems, enrichment tools, lead scoring models, and conversational interfaces that help reps work smarter.
• Translate business requirements into technical solutions. Deeply understand sales workflows and pain points to build tools that actually get used. Collaborate closely with the GTME sales team to uncover new data-driven opportunities.
• Develop predictive models and scoring systems using SQL, Python, and ML frameworks to identify high-intent prospects, forecast pipeline, and optimize GTM motions.
• Create feedback loops and measurement frameworks to track the impact of GTME and enablement solutions you’ve helped launch — from adoption metrics to revenue influence to rep productivity gains.
• Ship internal tools that sales reps love — enrichment workflows, Slack bots, Chrome extensions, automated alerts, AI research assistants, and lightweight apps that reduce manual work.

Cross-Functional Collaboration

You'll work closely with three core teams:

• Sales: Act as an embedded technical partner to the sales organization and treat them as your primary stakeholder. Use direction from Sales leadership / GTME, and use their campaigns and app ideas as the basis of your roadmap. Align the success of your deliverable to metrics that align with the sales team’s success, including pipeline and rep efficiency.
• RevOps: Co-own data quality, lead scoring models, campaign measurement, and CRM hygiene. Ensure your analytics and tools integrate seamlessly with operational workflows.
• Special Projects: Collaborate on deploying and scaling agentic AI systems. Serve as the bridge between experimental AI capabilities and production sales applications. Provide feedback loops and real-world performance data.

What you'll need to be successful

• 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

Bonus points

• You've worked in an Analytics Engineering, Data Engineering, or RevOps role at a modern SaaS company
• You bring both deep technical skills AND GTM intuition — a rare combination that makes you incredibly effective
• You've thrived in a 0→1 environment and love building new systems from scratch
• You've built and deployed AI agents, workflow automations, or custom internal tools that drove measurable business impact
• You have experience with sales tech stacks (HubSpot, Salesforce, Outreach, Clay, etc.) and understand how data flows through GTM systems

$140,000 - $160,000 USD per year

The cash compensation range shown is a starting point. In addition to equity, benefits and perks, your cash compensation is subject to an annual review and increase on a once per year basis.