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Multiplier Holdings is a VC-backed startup acquiring and scaling professional services firms through AI and automation, operating in regulated verticals like tax and corporate accounting. Unlike traditional software vendors, Multiplier combines technology and service delivery in-house, building custom AI and workflow components to boost efficiency for clients and staff.
The company organizes engineering into vertically-owned "pods"—cross-functional teams embedded in specific business domains (tax, corporate accounting, firm operations) that own product areas end-to-end. Pods move fast because they operate independently, talking directly to the firms and staff they serve, deciding what to build, and shipping it without waiting on a central roadmap.
As a Founding Product Engineer, you will own problems end-to-end: conduct discovery conversations with operators and accountants, decide what's worth building, design systems, and execute full-stack implementation. You'll be dropped into high-value problem areas with no existing spec and take them from discovery to production within weeks.
Key responsibilities include running discovery conversations directly with users, turning feedback into scoped objectives and prioritized roadmaps, designing and shipping agentic AI workflows (LLM agents, extraction pipelines, human-in-the-loop review), owning full-stack product surfaces (backend APIs, React frontends, configurable templates, document workflows), and writing technical design docs that align other pods and domain experts.
You should have 8+ years building software with founding or early-startup experience. You think like a founder—given a fuzzy problem and no roadmap, you figure out what's actually happening, place a bet, and build rather than wait for specs. You have a track record of owning outcomes end-to-end, from ill-defined problems through shipped software with real prioritization calls. You're resourceful, comfortable shipping scrappy solutions today rather than waiting for perfect setups. You move comfortably across the full stack (backend, APIs, data models, frontend, production debugging) and have hands-on production experience with LLMs and agents, including orchestration, tool use, and human-in-the-loop design. You're comfortable working directly with non-technical domain experts and are a strong technical communicator who writes crisp design docs and aligns teams around paths forward.
This is not a ticket-execution role, not a research-only AI position, and not an internal platform role—it's measured by direct customer value. You'll run a mini-startup inside a larger company at the intersection of financial data and applied AI, where correctness is non-negotiable. You'll shape both product direction and technical foundation, seeing firsthand whether professionals trust what you build.
