AI Data Engineer (Agent Platform)

About Collective:

Collective is on a mission to redefine the way businesses-of-one work. Our technology and team of trusted advisors help members achieve financial independence by taking care of everything from business incorporation to accounting, bookkeeping, tax services, and access to a thriving community, all in one integrated platform. We believe in empowering self-employed people to enjoy the same tax savings that big companies get, so they can focus on their passion, not paperwork.

Featured in Forbes, Business Insider, Yahoo, Bloomberg, Financial Times, TechCrunch, and more. We are backed by General Catalyst, Sound Ventures (Ashton Kutcher and Guy Oseary), QED Investors, Google’s Gradient Ventures, Expa, and other investors who have financed iconic companies like YouTube, Substack, Twitch, Box, Hims, Instacart, and Lyft.

About the role:

Most teams have the data they need but can’t access it. This role is here to fix that.

We're hiring a senior engineer to build an internal data agent: a system that lets anyone at the company act as their own data analyst. Individuals can ask questions in plain English and get back correct, decision-ready answers or dashboards.

This is not a traditional data role. You'll operate across AI systems, data infrastructure, and product engineering. You'll be responsible both for building a powerful system and for ensuring the data it relies on is clean, consistent, and reliable.

The problem space is wide open. We’re looking for a strategic operator to shape the technical direction, the data model, and system adoption.

What you'll do: 

•  Build an end-to-end analytics system

  • Create a natural language interface over our entire data stack

  • Enable anyone to run complex analyses without writing SQL

• Own and improve the data layer

  • Collaborate with product engineering to design and evolve clean, consistent data models

  • Identify inconsistencies in the core schema and resolve them at the source

• Build and maintain data pipelines

  • Own the reliability of our data infrastructure end-to-end

  • Debug and fix broken systems (e.g. dbt models, pipeline failures)

  • Make it easy to integrate new data sources into the data warehouse

• Develop agent infrastructure

  • Build retrieval, planning, and execution systems on top of real data

  • Support multi-step reasoning and analysis workflows

  • Integrate into internal tools

• Make it trustworthy

  • Ensure outputs are correct, consistent, and explainable

  • Build evaluation loops, monitoring, and guardrails

  • Eliminate ambiguity in metrics, definitions, and sources of truth

  • Handle permissions, sensitive data, and edge cases

• Drive adoption

  • Work directly with teams across EPD, Member Operations, Legal, and more

  • Drive alignment on data definitions and system usage

  • Turn this into the default way people interact with data

What you'll bring:

•  You are a product engineer working in data

  • You treat data models as part of the product, not a separate layer

  • You have strong opinions on schema design, naming, and consistency

  • You're comfortable identifying issues in production data and fixing them at the root

• You are an owner, not a participant

  • You take vague, high-stakes problems and turn them into real systems

  • You care about outcomes, not just implementation

• You have strong data experience

  • Experience with data modeling, warehouses, and pipelines

• You're an exceptional builder

  • You can go from idea → architecture → production

  • You've built with LLMs, RAG, or agents in production

  • You've shipped systems that people actually rely on

• You have influence

  • You communicate effectively with both technical and non-technical stakeholders

  • You can drive alignment across teams with competing priorities

  • You're comfortable challenging existing systems and pushing for better approaches

• You have taste

  • You know the difference between something that works and something people trust

  • You make pragmatic tradeoffs without overengineering

• You move fast

  • You default to action and iteration

  • You're comfortable operating independently

What we offer:

• Hybrid Work Model: Based in San Francisco with a balance of in-office and remote flexibility.

• Fresh Lunch: Provided on in-office days.

• Commuter Support: $150 monthly reimbursement for transit expenses.

• Health & Wellness: $200 quarterly reimbursement to support your well-being.

• Time Off: Flexible PTO plus 14 company holidays.

• Comprehensive Coverage: 100% medical, dental, and vision for employees; 75% coverage for dependents.

• Parental Leave: 16 weeks fully paid.

• Retirement & Ownership: 401k plan plus an equity package.

• Team Connection: Quarterly virtual events and an annual in-person summit.