Forward Deployed Engineer - Private Equity

Build production software for some of the most sophisticated investors in the world.

This is a software engineering role for someone who likes getting close to the people using what they build.

You’ll write production code, work through complicated data problems, and partner directly with private equity, private credit, and venture capital firms. You’ll also bring what you learn back to the product team and help turn one customer’s difficult problem into something the broader platform can solve.

It is not a traditional sales engineering position.

It is not customer success with some coding attached.

The simplest description is:

Investment firms operate on enormous amounts of valuable information, but that information rarely lives in one clean system. It may be spread across databases, spreadsheets, documents, internal knowledge repositories, third-party platforms, and years of inconsistent processes.

This company is building AI-native data infrastructure to make that information usable.

The core platform already exists. The challenge is making it work against the real-world data, systems, and workflows of each customer.

That is where you come in.

You’ll work with customers to understand what they are actually trying to accomplish, build the technical solution, and help determine which parts should eventually become reusable product capabilities.

• Connect structured and unstructured data from several customer systems.
• Build a custom workflow using Python, SQL, and modern AI infrastructure.
• Turn an unclear customer request into a working prototype.
• Develop a technical demonstration using the customer’s actual data.
• Take an early solution from prototype through production.
• Work with founders and engineers on the right architecture.
• Identify a recurring customer need that should become part of the core product.
• Explain a technical decision to both an engineer and an investment professional.
• Move between backend development, data modeling, product thinking, and customer conversations in the same week.

You will still write code.

That point matters.

The company is not looking for someone who used to be an engineer and gradually moved into meetings, account management, or technical sales. It wants an engineer who can build meaningful software and also enjoys seeing firsthand how that software gets used.

Meet with a private investment firm to understand why an important workflow still depends on several spreadsheets and a manual research process.

Explore the underlying data, map the relevant systems, and work through an architecture with the internal engineering team.

Build the first version in Python and SQL. Connect several structured data sources with information pulled from documents and internal knowledge.

Put the solution in front of the customer, learn where the original assumptions were wrong, and adjust quickly.

Ship the next iteration, document what should become reusable, and bring a product recommendation back to the founders.

Not every week will look like that.

That is partly the appeal—and partly the warning label.

This is an approximately $50 million Series A company building AI and data infrastructure for private-market investors.

The company is founder-led and engineering-driven, with teams in San Francisco and New York.

• Direct access to founders and product decision-makers.
• Short distances between an idea and a production release.
• Complicated customer data.
• Incomplete information.
• Fewer layers of process than you would find at a large company.
• The ability to influence both individual deployments and the direction of the product.

You will not be handed perfectly formed tickets for every problem.

You will be expected to understand the objective, make good technical decisions, communicate clearly, and keep moving.

The product is still evolving.

Customer environments can be messy.

Requirements may change once you see the real data.

Some solutions will begin as custom…