GC AI is the fastest-growing and most trusted legal AI platform for in-house legal teams. We're building the future of legal work, and we're doing it fast. You'll join at a pivotal moment—when decisions matter, impact is immediate, and the runway to shape your career is wide open. We’re a high-performing team where you'll have real ownership and influence from day one.
More than 1,800 companies use GC AI to drive their business forward, including 150+ public companies, 25+ unicorns, and brands such as News Corp, Miro, Bass Pro Shops, Snyk, Skims, Liquid Death, Vercel, Zscaler, and TIME.
We've 10x'd revenue in 12 months, raised a $60 million Series B ($555 million valuation), and are growing faster than ever. We are backed by incredible investors, including Scale Venture Partners, Northzone, Sound Ventures, and Guillermo Rauch, CEO of Vercel.
If you thrive when the stakes are high and the path isn't paved, you'll love it here. Our six guiding principles are: 1% better every day, customer obsession, ship today, find a way, care deeply, and own it completely. Come shape the future of legal work with us.
About The Role
We are seeking an Analytics Engineer to join Revenue Operations and build the intelligence layer that turns GC AI's data into decisions. Reporting to Emma Heist, Head of Revenue Operations, you will be GC AI's first dedicated analytics hire, working closely with Sales, Marketing, Customer Success, Finance, Product, and leadership to define how the company measures itself and where it focuses.
You won't be building the warehouse from scratch (our Data Engineering team owns that), but you will own everything that sits on top of it: the data models that reflect how the business actually works, the dashboards and reporting that teams rely on daily, the KPI frameworks that drive GTM strategy, and the self-serve analytics layer that lets anyone answer their own questions. You will also partner closely with Data Engineering to ensure the warehouse schema and pipeline design support the analytical use cases the business needs.
We're looking for someone who combines strong technical chops in SQL, data modeling, and BI tooling with genuine curiosity about business operations and a knack for translating messy business questions into clean analytical frameworks.
What You'll Do
Own the Analytical Modeling Layer: Design and maintain dimensional models (revenue, pipeline, product usage, retention, customer lifecycle) that make warehouse data usable for business teams. Partner with Data Engineering on schema design to ensure the warehouse serves analytical use cases.
Create the Intelligence Layer: Build dashboards, reports, and self-serve analytics that give Sales, Marketing, Customer Success, Product, Finance, and leadership real-time visibility into the metrics that matter. Define KPIs, build attribution models, and create the single source of truth for company performance.
Drive GTM Analytics: Own the analytical frameworks behind pipeline generation, sales forecasting, customer health scoring, retention analysis, and marketing attribution. Be the person who can tell the exec team not just what happened, but why, and what to do about it.
Build Analytics Workflows: Build lightweight transformation and enrichment pipelines specific to analytics workflows (e.g., attribution logic, cohort tagging, KPI rollups) using dbt or similar tools. Implement data quality checks and governance practices to keep analytics accurate and trustworthy as we scale.
Enable Data-Driven Culture: Partner with stakeholders across Revenue Operations, Finance, Product, and the exec team to understand their data needs, translate business questions into analytical frameworks, and make data accessible to non-technical users. You'll be the go-to person when someone asks, "Where does this number come from?"
Scale the Function: Establish standards, documentation, and best practices to enable GC AI's analytics capabilities to grow. As the first analytics hire, you'll shape the roadmap for the analytics function's evolution and help recruit the next members.
What You've Done
5+ years in data engineering, business intelligence, or analytics engineering roles in B2B SaaS, with hands-on experience building data infrastructure from early-stage or greenfield environments.
Experience building and maintaining analytical data models, semantic layers, or transformation layers using tools like dbt, Looker modeling, or similar frameworks.
Strong proficiency in SQL, with experience modeling data in cloud warehouses such as BigQuery or Snowflake. Working knowledge of Python for scripting and automation.
Track record building dashboards and reporting in BI tools (e.g., Looker, Tableau, or Sigma) that business teams rely on daily.
Experience working with data from multiple SaaS systems (CRM, billing, product analytics, support platforms) and building unified, governed analytical models on top of them.
Strong cross-functional collaboration with Sales, Marketing, Finance, Product, and leadership to align data work with business priorities and GTM goals.
Analytical mindset with expertise in defining and tracking KPIs (e.g., ARR, pipeline velocity, conversion rates, retention, NRR) and using data to optimize go-to-market performance.
Self-starter who thrives in fast-paced, ambiguous startup settings while balancing long-term architectural thinking with the need to ship today.
Nice to have
Experience working alongside a data engineering team to influence warehouse design from the analytics consumer's perspective.
Familiarity with product-led growth analytics, usage-based metrics, or AI/ML product instrumentation.
Experience with data governance, data contracts, or data observability tooling (e.g., Monte Carlo, Great Expectations).
We’re building something new in a once-in-a-generation shift in technology and the legal industry, so we move at a relentless pace. We expect urgency, ownership, and good judgment even when things aren’t perfectly clear. If you need structure and consensus to do your best work, this isn’t the right place for you. If you thrive in ambiguity and growth, work with intensity, and want real responsibility, keep reading. We’re excited to meet you.
Location PolicyThis is a remote role unless you fall within the following parameters. If you live within approximately 50 miles of our San Mateo, CA or Provo, UT office, the position follows a hybrid schedule with in-office days on Tuesdays, Wednesdays, and Thursdays.
GC AI is an equal opportunity employer that supports workplace diversity and does not discriminate on the basis of race, color, religion, gender identity/expression, national origin, age, military service eligibility, veteran status, sexual orientation, marital status, physical or mental disability, or any other protected class. GC AI is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. #LI-GCAI
To protect yourself against phishing and recruitment fraud, please note that GC AI only accepts job applications through our official careers page at https://gc.ai/careers and through sponsored jobs on LinkedIn. All legitimate communication from our team regarding job opportunities will come from a GC AI team member with a @gc.ai or @getgc.ai email address.
GC AI will never:
Refer you to external websites to apply
Conduct interviews over email, chat platforms, or messaging apps
Ask you to provide payment or purchase equipment
Request personal or financial information such as your mailing address, social security number, credit card numbers, or banking information during the application process
Examples of fraudulent email addresses:
Any email address ending in @gmail.com, @yahoo.com, or other free email services
If you are contacted by someone claiming to be from GC AI via an unofficial channel or from a suspicious email address, please do not share any information. Mark the communication as "phishing" or "spam" and do not respond.
Skills Required
- 5+ years in data engineering, business intelligence, or analytics engineering roles in B2B SaaS
- Experience building and maintaining analytical data models, semantic layers, or transformation layers using dbt, Looker modeling, or similar frameworks
- Strong proficiency in SQL and experience modeling data in cloud warehouses such as BigQuery or Snowflake
- Working knowledge of Python for scripting and automation
- Track record building dashboards and reporting in BI tools (Looker, Tableau, or Sigma)
- Experience working with data from multiple SaaS systems (CRM, billing, product analytics, support) and building unified analytical models
- Strong cross-functional collaboration with Sales, Marketing, Finance, Product, and leadership
- Expertise in defining and tracking KPIs (ARR, pipeline velocity, conversion, retention, NRR) and using data to optimize GTM
- Self-starter comfortable in fast-paced, ambiguous startup environments
- Experience influencing warehouse design from analytics consumer perspective
- Familiarity with product-led growth analytics, usage-based metrics, or AI/ML product instrumentation
- Experience with data governance, data contracts, or data observability tooling (Monte Carlo, Great Expectations)
GC AI Compensation & Benefits Highlights
How does GC AI ensure its pay and bonus plans are competitive?
GC AI ensures its pay and bonus plans are competitive through a structured and transparent compensation approach. The company publishes pay transparency, uses defined pay bands with transparent earning potential, and sets defined commission tiers and policies for applicable roles. Its compensation package also includes company equity and a 401(k), giving employees a clear view of both immediate pay and long-term financial upside.
GC AI reinforces that compensation philosophy with practices that create consistency and clarity across the employee experience. The company promotes from within, supports learning and development, and maintains defined working hours, availability expectations, and goal-setting through an OKR operating model. For job seekers, that signals a workplace where compensation is tied to clearly established expectations, growth opportunities, and a rewards structure designed to stay competitive as the company scales.
GC AI Insights
What We Do
GC AI is the leading legal AI platform built specifically for in-house teams to solve the high-precision workflows they face every day. With powerful features like Easy Prompt™, Exact Quote™ citations, and native Microsoft Word integration, GC AI enables legal professionals to be strategic business partners through faster and more accurate drafting, reviewing, researching, and redlining. Purpose-built for sensitive, high-stakes matters, the platform leverages five large language models while maintaining enterprise-grade security as a SOC 2 Type II certified provider that never uses confidential data for training. Founded by three-time General Counsel Cecilia Ziniti and AI engineer Bardia Pourvakil, GC AI is trusted by over 1,600 legal teams globally, including brands like News Corp, Skims, TIME Inc., Liquid Death, and Vercel. Discover the difference of becoming an AI-powered lawyer. Try it free or book a demo at gc.ai.
Why Work With Us
GC AI offers a rare opportunity to join a high-growth category leader at the intersection of generative AI and deep legal expertise. Our culture is defined by a "1% better every day" philosophy, favoring curious, customer-obsessed builders who thrive in a high-ownership environment where they can see the immediate impact of their work.
Gallery
GC AI Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
Many roles are eligible for remote work in the U.S. and Canada. For folks who live within 50 miles of our San Mateo, CA, or Provo, UT offices, we value in-person collaboration and work in the office on Tuesday, Wednesday, and Thursday.

