Founding Engineer | $150k-$230k | AI × Private Equity

About the job

This is a CoffeeSpace Partner Role. CoffeeSpace works with a small number of early-stage founders building ambitious companies and helps them find their founding hires through a curated network and semantic matching.

This particular role is with a stealth, SF-based startup building AI-native infrastructure to automate critical private equity workflows.

If there’s a strong fit, you’ll start with a conversation via CoffeeSpace, followed by direct conversations with the founding team.

TL;DR

• Role: Founding Engineer (early technical hire)

• Comp: $150k–$230k cash + meaningful founding equity

• Location: San Francisco (in-person preferred)

• Stage: Early revenue, raised several million from a top AI-focused fund

• Domain: AI agents × private equity workflows

This is a true 0→1 founding role with deep ownership across architecture, infra, and product.

The problem

Private equity teams spend enormous amounts of time on manual, high-stakes workflows:

• Parsing unstructured deal documents

• Digging through fragmented financial data

• Running repetitive analyses

• Drafting investment memos, LP updates, and internal artifacts

These tasks are mission-critical — but today they’re still handled with spreadsheets, PDFs, and human glue work.

The result: slower deal cycles, higher costs, and teams that don’t scale.

The opportunity

This startup is building an AI-native infrastructure layer for private equity — designed from the ground up for agentic workflows.

What that includes:

• AI-powered parsing of deal docs and financial data

• Automated generation of research and investment artifacts

• Workflow agents that support real-time decision-making

• Secure, compliant systems built for institutional-grade use

The goal: automate what’s currently unscalable and unlock step-function gains in how deals get done.

The founding team

• CTO: Ex-Uber senior engineer and tech lead, with deep experience in large-scale infrastructure and safety-critical systems

• CEO: Former private equity investor at a top global fund and ex-McKinsey strategy consultant, with firsthand experience inside PE workflows

Together, they’ve:

• Closed high five-figure revenue in their first month

• Raised several million dollars from a top-tier AI-focused venture fund

• Built early customer momentum in a notoriously hard market

The role

As a Founding Engineer, you’ll:

• Build and scale end-to-end systems powering AI agents for PE workflows

• Architect data pipelines for parsing, entity extraction, and structured outputs

• Design real-time analysis tools and internal dashboards for PE operators

• Integrate LLMs into knowledge retrieval, document automation, and workflow orchestration

• Partner directly with the founders to iterate quickly toward product–market fit

This is a high-agency role with real technical and product ownership from day one.

The ideal candidate

You’ll likely be a strong fit if you:

• Are a full-stack or backend-leaning engineer (Python, TypeScript, infra)

• Are hands-on with LLMs, RAG, or agentic workflows

• Thrive in ambiguous, fast-moving 0→1 environments

• Ship quickly and take ownership of outcomes, not just tasks

Nice to have (not required):

• Fintech, enterprise SaaS, or workflow automation experience

• Exposure to regulated or compliance-heavy environments

You should be ready to go full-time in the next 1–2 months if there’s strong mutual fit.

What you’ll get

• Above-market compensation: $150k–$230k cash + meaningful founding equity

• Deep ownership across architecture, infra, and product design

• Direct collaboration with experienced, high-trust founders

• A mission with long-term defensibility in a massive market

Why this matters

Private equity is a $4T+ industry still run on manual, people-heavy workflows.

This company is building the agentic infrastructure to modernize how deals get done — automating the unscalable and reshaping one of the most important financial ecosystems in the world.