Senior AI Product Engineer
About the company
Turning marketing into a market-domination weapon, we created a new category — the marketplace for future customers. Businesses shop for leads as they shop for products in e-commerce: you see everything about a lead before you buy — full transparency, control, and predictable outcomes. We're the #1 lead marketplace in the USA, and we're accelerating.
Role overview
We're looking for a Senior AI Product Engineer to build the AI operating layer behind our marketplace. You take a valuable but unclear business problem — improve lead quality, cut refunds, automate a manual workflow, extract intelligence from calls — and turn it into a dependable production system end-to-end: investigate, define success, design, build, deploy, and improve on real usage data. You are a one-person AI product team for high-leverage problems, not a spec-taker.
We are expanding beyond real estate into new service-business niches, and growth is powered by reusable software and automation — not proportional growth in manual work. Every system you ship either compounds into that leverage or exposes where it leaks — no in-between.
Why this role exists
Our growth is not limited by ideas or data — we already run 40K+ members, 750+ verified daily leads, and 50B data points powering AI. It's limited by how fast we can turn ambiguous, high-value problems into shipped AI systems that actually move business metrics. We need a builder who owns the complete production outcome — not a prompt tinkerer, not a researcher, not a PM who delegates the build.
Requirements:
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Strong record of building and shipping production software end-to-end, ideally in a SaaS, marketplace, or workflow product — with real users and real revenue on the line.
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Strong Python and/or TypeScript, plus solid backend fundamentals: APIs, databases, auth, data models, testing, and deployment.
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Hands-on experience shipping LLM-powered functionality using model APIs, structured outputs, tool/function calling, retrieval, context engineering, and agentic workflows.
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Production automation experience: webhooks, events, queues, schedules, retries, idempotency, monitoring, and failure recovery — not just happy-path demos.
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Practical evaluation skills: test sets, traces, quality metrics, regression checks, feedback loops, and root-causing real production failures.
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Daily fluency with AI coding agents (Claude Code, Codex, Cursor, or equivalent) — you review, test, refactor, and secure generated work, not ship it raw.
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English C1+; our stakeholders, users, and business owners are US-based, and communication must be sharp and clear.
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AI-first by default — if you are not already using AI to 3x your own output, you will be behind the rest of engineering.
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Product ownership and strong judgment in ambiguous, fast-moving environments — you clarify goals, make tradeoffs, and connect every technical decision to a business KPI.
What You'll Be Doing:
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Discover high-value product and operational problems by working directly with users, business owners, and internal teams, then frame clear success criteria before writing code.
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Design and ship customer-facing AI features and internal automations across lead quality, matching, prediction, call intelligence, CRM, support, and operations.
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Build agents and workflows that safely use tools, APIs, databases, calls, SMS, email, and other company systems — with human approval where risk requires it.
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Create the context layer around models: instructions, retrieval, memory, structured outputs, tool definitions, permissions, and feedback loops.
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Build reliable event-driven and scheduled automation using webhooks, queues, schedulers, retries, idempotency, audit logs, and graceful fallbacks.
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Create evaluation datasets and automated checks that measure usefulness, accuracy, failure modes, regressions, latency, and cost — before and after release.
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Investigate real production failures and improve the complete syst