Senior Software Engineer (Product)

ActiveProspect · United States · posted 689mo ago

engineering javascript python remote jobs in united states

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About this role

Senior Product Engineer

Company Overview

ActiveProspect is on a mission to make consent-based marketing the best channel for online customer acquisition. We provide marketers the products they need to acquire qualified customers at scale. Our platform is trusted by thousands of companies engaged in direct-to-consumer marketing, helping them save wasted spend, comply with ever-changing regulations, and manage a constantly evolving partner landscape. Our flagship product, TrustedForm, is used to certify over 1 billion opt-in digital customer leads every year and is the gold standard for documenting prior express written consent for TCPA compliance.

Job Summary

You own customer and business outcomes, not tickets. You work like a forward-deployed engineer: your home base is a core team, and you deploy into projects, initiatives, and pods where the problem is, ship the outcome across the full stack (React on the frontend, Node.js and Python services on AWS), then carry what you learned back so the next team moves faster.. The technical bar is high, but coding ability is the floor here, not the ceiling. What sets this role apart is judgment: knowing the smallest thing worth shipping, when to kill your own idea, and when AI output is good enough versus when to override it.

You'll move between your home team and the initiatives you deploy into, shipping early, talking to customers, and deciding fast.

Responsibilities

Own outcomes end-to-end, wherever you're deployed. Frame the problem, design it, ship it, own the metric. Descope to the cheapest version that works. Prototype in days.
Stay close to customers. Shadow sales and support, join advisory conversations, and let customer reality drive technical decisions. Propose what to build, defer, and kill.
Own your domain and share it. Its interfaces, reliability, performance, and security, including on-call for the systems you own. Consent and PII handling are central to customer trust. Bring patterns, tooling, and hard-won context back to the wider org rather than hoarding them.
Build and scale both the product surface and the platform beneath it. Ship responsive, accessible React interfaces with a strong UI/UX eye, back them with Node.js and Python services and APIs, and keep the cloud batch platform and data pipelines that deliver multi-tenant products reliable as they scale.
Architect AI-driven leverage. Build AI-assisted workflows that hold up, evolve the team's practices as tooling changes (Cursor, Claude Code, and whatever comes next), and look for product wins AI unlocks (smarter routing, anomaly detection, and more).
Multiply the teams you touch. Mentor on judgment and product sense, not just syntax. Write decision memos and ADRs. Enable Product and Design to self-serve.

Qualifications and Skills

A track record of shipping something end-to-end that you cared about and owning the outcome, not just the code.
Product judgment: pushing back on a bad spec, proposing the cheapest experiment, descoping well, and collaborating with Product to suggest solutions rather than waiting for a fully specced ticket.
Comfort embedding with unfamiliar teams and codebases, getting productive fast, and leaving them better than you found them.
Deep full-stack expertise: React (component lifecycle, state management, rendering optimization), JavaScript/TypeScript, and modern CSS on the frontend; Node.js and Python services, RESTful APIs, and asynchronous data handling on the backend.
Cloud and data-pipeline depth: AWS core services (Lambda, EC2, S3, DynamoDB, API Gateway) and cloud batch / workflow orchestration (Step Functions, Airflow, or similar) to deliver multi-tenant batch products and data solutions reliably at scale.
A strong UI/UX eye: you turn wireframes, mockups, and ambiguous requirements into intuitive, accessible, user-centric journeys.
Strong systems design judgment in ambiguous contexts, and a security mindset aligned with sensitive consumer data and compliance.
Fluency building your own AI-assisted workflows and reading AI output critically. Daily use of AI-native tools (Cursor, Claude Code) and precise prompting across OpenAI and Claude models, with the judgment to know when to trust output, how to review it for hidden bugs and security issues, and when to override it.
Clear written and verbal communication. Mentorship experience. 5-10% travel.

How It Works

You'll report to an Engineering Manager who owns several teams and stays out of their daily flow. As you embed, you'll often act as the player-coach Tech Lead, owning technical direction while the EM owns delivery health and stakeholder alignment across the group.

Success looks like movement in a user or business metric you/your team owns, high-value work deliberately not built, decisions made fast, and teams that move faster after you've worked with them, not just while you're there.