Forward Deployed Engineer

Forward Deployed Engineer Build production software for some of the most sophisticated investors in the world. San Francisco or New York | Full-Time | Early-Stage AI Company | Equity Included 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: A software engineer who enjoys working with customers. Why this role exists 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. What you’ll really do You might: 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. A week might include Monday Meet with a private investment firm to understand why an important workflow still depends on several spreadsheets and a manual research process. Tuesday Explore the underlying data, map the relevant systems, and work through an architecture with the internal engineering team. Wednesday Build the first version in Python and SQL. Connect several structured data sources with information pulled from documents and internal knowledge. Thursday Put the solution in front of the customer, learn where the original assumptions were wrong, and adjust quickly. Friday 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. The engineering environment 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. You should expect: Significant ownership.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 honest part: 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 work before the team understands how to make them reusable. You may spend part of a day discussing a workflow with a customer and the rest of it debugging a data issue or writing production code. There will be ambiguity, context switching, and moments when the answer is not obvious. For the right engineer, that is interesting. For someone who wants tightly defined responsibilities, extensive process, and long planning cycles before anything is built, it may be exhausting. You’ll probably thrive here if: You are unquestionably a software engineer first.You have personally designed, built, and owned production systems.You are strong in backend or full-stack development.You can take an incomplete problem and independently move toward a solution.You enjoy speaking directly with users rather than receiving every requirement secondhand.You can explain technical decisions without hiding behind jargon.You like seeing the practical result of what you build.You have worked in a startup, founding environment, or another setting with significant ownership.You are comfortable crossing the boundaries between engineering, data, product, and customer work.You want your work to influence the product—not simply implement what has already been decided. The likely experience range is approximately three to eight years, although demonstrated ownership matters more than matching an exact number. This probably isn’t for you if: You want to move away from hands-on engineering.Your recent experience has primarily been pre-sales, account management, customer success, or high-level consulting.You prefer clearly separated engineering and customer-facing teams.You need complete requirements before you can begin.You are uncomfortable showing unfinished work, gathering feedback, and iterating.You prefer large-company specialization over early-stage ownership.You like the Forward Deployed Engineer title more than the actual work. Technical context The most relevant foundation includes: PythonSQLBackend or full-stack software engineeringData modelingData infrastructureProduction system ownership Experience with the following would be valuable: Large language modelsRetrieval-augmented generationEmbeddingsVector databasesAgentic workflowsAI-native product developmentModern frontend development Experience in private equity, private credit, venture capital, or financial services can help, but it is not the main qualification. The company would rather hire an excellent engineer who can learn the domain than a domain specialist who is not strong enough technically. What makes this worth considering A lot of engineering roles promise ownership. Here, ownership means working directly on difficult customer problems, building the solution yourself, and then helping decide how those lessons should change the product. You’ll be close to: The customers.The code.The founders.The product decisions.The commercial impact of your work. You will have a chance to build practical AI systems that move beyond demos and operate inside real investment workflows. That combination is unusual: meaningful engineering depth, direct customer exposure, and genuine product influence. Compensation and logistics Employment: Full-timeLocations: San Francisco and New YorkWork model: On-siteCompensation: $150,000 – $275,000 Equity: IncludedBenefits Included We believe candidates deserve clarity around compensation and working expectations. Those details will be added before this brief is published rather than buried later in the interview process. A note from Epic Placements We have been recruiting for more than two decades, and we know that changing jobs—especially to join an early-stage company—is a meaningful decision. Our job is not to pressure you into an interview or manufacture urgency. It is to give you an honest view of the opportunity, answer what we can, and help both sides determine whether there is a real fit. This role will not appeal to every strong engineer. But if you like building production software, solving messy problems, working directly with users, and having a visible effect on a young product, it is worth a conversation.