CTO / Lead Engineer, Thirdbase Capital

About Thirdbase Capital

Thirdbase Capital is a growth-stage venture platform investing in AI, defense, frontier tech, robotics, energy, and fintech. Our portfolio includes some of the most sought-after private companies in AI and deep tech. We are now building the internal technology that will define how we source and underwrite the next decade of investments.

The Role

We are hiring a founding engineer to build Thirdbase Intelligence, a proprietary system that helps us identify exceptional growth companies earlier than conventional investors.

The system will measure where top talent is moving, how product and AI usage is accelerating, and whether that activity is converting into durable revenue. The north-star question it must answer: "What private company is becoming dramatically better, faster than the market realizes, and what objective evidence proves it?"

This is a data-engineering-first mandate. You will begin with the longitudinal data model, entity resolution, ingestion pipelines, and scoring methodology, and add a natural-language interface once the data foundation is solid. The full technical scope will be shared with shortlisted candidates.

What You'll Work On

Designing a longitudinal data model that tracks companies, people, roles, and career transitions over time

Building reliable ingestion pipelines for licensed workforce, hiring, web, and developer-activity datasets

Entity resolution across messy real-world data at the scale of millions of companies and profiles

Quantitative scoring and ranking methodologies, with backtesting against historical investment outcomes

A secure, read-only connector framework for structured diligence on companies raising capital

An evidence-grounded query and alerting layer on top of the data platform, built with modern LLM tooling

What We're Looking For

5+ years building data-intensive systems: pipelines, entity resolution, time-series infrastructure, and graph data models at scale

Strong backend engineering (Python and/or a systems language; SQL; modern orchestration and warehouse tooling)

Experience integrating third-party data APIs and building monitored, production-grade ingestion for imperfect datasets

Practical experience with LLM application development, including retrieval, structured outputs, and agentic workflows

Ability to design scoring and ranking methodologies and validate them empirically

A security-conscious mindset for handling sensitive third-party data under strict access controls and licensing terms

Self-direction, with the ability to own architecture end-to-end and work directly with the investment team

Nice to Have

Prior work on people or workforce data, alternative data for investing, or data platforms at growth or hedge funds

Experience building secure customer-facing data connectors (OAuth, read-only scopes, audit logging)

Background in quantitative research, recommender systems, or anomaly detection

Why This Role

You will own a greenfield build with direct impact on real investment decisions, work closely with the fund's partners, and create a system that compounds in value with every week of data collected. This is a chance to build the kind of proprietary infrastructure most funds only talk about.

How to Apply

Send your CV or portfolio along with brief answers to the following to [hidden]:

Describe the most complex data system you have built: its architecture, scale, and the hardest problem you solved.

If you had to merge person-level records from three overlapping datasets with inconsistent identifiers, how would you approach entity resolution and measure its accuracy?